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Dept: Biomedical Engineering

You searched for subject:( classification). Showing records 1 – 27 of 27 total matches.

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University of Minnesota

1. Moghimi, Pantea. Novel Biomarker Identification Approaches for Schizophrenia using fMRI and Retinal Electrophysiology.

Degree: PhD, Biomedical Engineering, 2017, University of Minnesota

 Schizophrenia is a chronic mental illness. The exact cause if schizophrenia is not yet known. Extensive research has been done to identify robust biomarkers for… (more)

Subjects/Keywords: Classification; Cross Validation; fMRI; Retina; Schizophrenia

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APA (6th Edition):

Moghimi, P. (2017). Novel Biomarker Identification Approaches for Schizophrenia using fMRI and Retinal Electrophysiology. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/193420

Chicago Manual of Style (16th Edition):

Moghimi, Pantea. “Novel Biomarker Identification Approaches for Schizophrenia using fMRI and Retinal Electrophysiology.” 2017. Doctoral Dissertation, University of Minnesota. Accessed November 17, 2019. http://hdl.handle.net/11299/193420.

MLA Handbook (7th Edition):

Moghimi, Pantea. “Novel Biomarker Identification Approaches for Schizophrenia using fMRI and Retinal Electrophysiology.” 2017. Web. 17 Nov 2019.

Vancouver:

Moghimi P. Novel Biomarker Identification Approaches for Schizophrenia using fMRI and Retinal Electrophysiology. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/11299/193420.

Council of Science Editors:

Moghimi P. Novel Biomarker Identification Approaches for Schizophrenia using fMRI and Retinal Electrophysiology. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/193420


University of Manitoba

2. Dastgheib, Zeinab. The use of spontaneous vestibular response for diagnosis of meniere’s disease.

Degree: Biomedical Engineering, 2016, University of Manitoba

 Meniere's disease is a common inner ear disorder that affects balance and hearing. Electrovestibulography (EVestG) is a relatively new vestibular driven test that measures spontaneous… (more)

Subjects/Keywords: Meniere's Disease; Classification; Fractal Dimension; Electrovestibulography

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APA (6th Edition):

Dastgheib, Z. (2016). The use of spontaneous vestibular response for diagnosis of meniere’s disease. (Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/31654

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Dastgheib, Zeinab. “The use of spontaneous vestibular response for diagnosis of meniere’s disease.” 2016. Thesis, University of Manitoba. Accessed November 17, 2019. http://hdl.handle.net/1993/31654.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Dastgheib, Zeinab. “The use of spontaneous vestibular response for diagnosis of meniere’s disease.” 2016. Web. 17 Nov 2019.

Vancouver:

Dastgheib Z. The use of spontaneous vestibular response for diagnosis of meniere’s disease. [Internet] [Thesis]. University of Manitoba; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1993/31654.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dastgheib Z. The use of spontaneous vestibular response for diagnosis of meniere’s disease. [Thesis]. University of Manitoba; 2016. Available from: http://hdl.handle.net/1993/31654

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Akron

3. Jose, Adarsh. Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date.

Degree: MSin Engineering, Biomedical Engineering, 2009, University of Akron

  Selecting a set of highly discriminant genes for biological samples is an important task for designing highly efficient classifiers using DNA microarray data. The… (more)

Subjects/Keywords: Biomedical Research; discrete wavelet transform; microarray data; cancer; gene selection; classification

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APA (6th Edition):

Jose, A. (2009). Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1240851642

Chicago Manual of Style (16th Edition):

Jose, Adarsh. “Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date.” 2009. Masters Thesis, University of Akron. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1240851642.

MLA Handbook (7th Edition):

Jose, Adarsh. “Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date.” 2009. Web. 17 Nov 2019.

Vancouver:

Jose A. Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date. [Internet] [Masters thesis]. University of Akron; 2009. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1240851642.

Council of Science Editors:

Jose A. Gene Selection by 1-D Discrete Wavelet Transform for Classifying Cancer Samples Using DNA Microarray Date. [Masters Thesis]. University of Akron; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1240851642


University of California – Irvine

4. Szymanska, Agnieszka Anna Fielder. Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing.

Degree: Biomedical Engineering, 2017, University of California – Irvine

 Electrophysiological signal processing is a broad, complex and growing field. Universally, the first steps of any signal analysis are detection and classification. Here we present… (more)

Subjects/Keywords: Biomedical engineering; Neurosciences; Anesthesia; Classification; Detection; MUA; Neuroengineering; Signal Processing

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APA (6th Edition):

Szymanska, A. A. F. (2017). Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/98t9n6c4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Szymanska, Agnieszka Anna Fielder. “Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing.” 2017. Thesis, University of California – Irvine. Accessed November 17, 2019. http://www.escholarship.org/uc/item/98t9n6c4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Szymanska, Agnieszka Anna Fielder. “Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing.” 2017. Web. 17 Nov 2019.

Vancouver:

Szymanska AAF. Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing. [Internet] [Thesis]. University of California – Irvine; 2017. [cited 2019 Nov 17]. Available from: http://www.escholarship.org/uc/item/98t9n6c4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Szymanska AAF. Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing. [Thesis]. University of California – Irvine; 2017. Available from: http://www.escholarship.org/uc/item/98t9n6c4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of California – Irvine

5. Cao, Liyu. Support Vector Machine for Kidney Cancer Classification.

Degree: Biomedical Engineering, 2018, University of California – Irvine

 Renal cancer is the 12th leading cause of cancer death, accounting for 2.4 percent of all cancers in the United States. Two of most common… (more)

Subjects/Keywords: Biomedical engineering; Bioinformatics; Cancer; Classification; Kidney; Support vector machine

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APA (6th Edition):

Cao, L. (2018). Support Vector Machine for Kidney Cancer Classification. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/2gg018np

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Cao, Liyu. “Support Vector Machine for Kidney Cancer Classification.” 2018. Thesis, University of California – Irvine. Accessed November 17, 2019. http://www.escholarship.org/uc/item/2gg018np.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Cao, Liyu. “Support Vector Machine for Kidney Cancer Classification.” 2018. Web. 17 Nov 2019.

Vancouver:

Cao L. Support Vector Machine for Kidney Cancer Classification. [Internet] [Thesis]. University of California – Irvine; 2018. [cited 2019 Nov 17]. Available from: http://www.escholarship.org/uc/item/2gg018np.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cao L. Support Vector Machine for Kidney Cancer Classification. [Thesis]. University of California – Irvine; 2018. Available from: http://www.escholarship.org/uc/item/2gg018np

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Iowa

6. Yavarna, Tarunashree. Airway segmentation of the ex-vivo mouse lung volume using voxel based classification.

Degree: MS, Biomedical Engineering, 2010, University of Iowa

  The spread of the pulmonary disease among humans is a very rapid process and it stands as the third highest killer in the United… (more)

Subjects/Keywords: Airways; excised Mouse; segmentation; voxel classification; Biomedical Engineering and Bioengineering

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APA (6th Edition):

Yavarna, T. (2010). Airway segmentation of the ex-vivo mouse lung volume using voxel based classification. (Masters Thesis). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/909

Chicago Manual of Style (16th Edition):

Yavarna, Tarunashree. “Airway segmentation of the ex-vivo mouse lung volume using voxel based classification.” 2010. Masters Thesis, University of Iowa. Accessed November 17, 2019. https://ir.uiowa.edu/etd/909.

MLA Handbook (7th Edition):

Yavarna, Tarunashree. “Airway segmentation of the ex-vivo mouse lung volume using voxel based classification.” 2010. Web. 17 Nov 2019.

Vancouver:

Yavarna T. Airway segmentation of the ex-vivo mouse lung volume using voxel based classification. [Internet] [Masters thesis]. University of Iowa; 2010. [cited 2019 Nov 17]. Available from: https://ir.uiowa.edu/etd/909.

Council of Science Editors:

Yavarna T. Airway segmentation of the ex-vivo mouse lung volume using voxel based classification. [Masters Thesis]. University of Iowa; 2010. Available from: https://ir.uiowa.edu/etd/909


University of Akron

7. Sewak, Mihir S. Application of Committee Neural Networks for Gene Expression Based Leukemia Classification.

Degree: MSin Engineering, Biomedical Engineering, 2008, University of Akron

 The present study was an effort to design a Committee Neural Networks-basedclassification system to subcategorize leukemia cancer data. The need for automatedclassification arose from the… (more)

Subjects/Keywords: Bioinformatics; Biomedical Research; Machine Learning; Neural Networks; Cancer; Leukemia; Committee; Classification; T Cell; B Cell

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APA (6th Edition):

Sewak, M. S. (2008). Application of Committee Neural Networks for Gene Expression Based Leukemia Classification. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1205514796

Chicago Manual of Style (16th Edition):

Sewak, Mihir S. “Application of Committee Neural Networks for Gene Expression Based Leukemia Classification.” 2008. Masters Thesis, University of Akron. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1205514796.

MLA Handbook (7th Edition):

Sewak, Mihir S. “Application of Committee Neural Networks for Gene Expression Based Leukemia Classification.” 2008. Web. 17 Nov 2019.

Vancouver:

Sewak MS. Application of Committee Neural Networks for Gene Expression Based Leukemia Classification. [Internet] [Masters thesis]. University of Akron; 2008. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1205514796.

Council of Science Editors:

Sewak MS. Application of Committee Neural Networks for Gene Expression Based Leukemia Classification. [Masters Thesis]. University of Akron; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1205514796


Wright State University

8. Crossen, Samantha Lokelani. Investigation of Variability in Cognitive State Assessment based on Electroencephalogram-derived Features.

Degree: MSEgr, Biomedical Engineering, 2011, Wright State University

 To implement adaptive aiding in modern aviation systems there is a need for accurate and reliable classification of cognitive workload. Using electroencephalogram (EEG)-derived features, it… (more)

Subjects/Keywords: Biomedical Research; Electroencephalogram (EEG); Artificial Neural Network (ANN); AdaBoost Algorithm; Workload Classification; Feature Variability

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APA (6th Edition):

Crossen, S. L. (2011). Investigation of Variability in Cognitive State Assessment based on Electroencephalogram-derived Features. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1316025164

Chicago Manual of Style (16th Edition):

Crossen, Samantha Lokelani. “Investigation of Variability in Cognitive State Assessment based on Electroencephalogram-derived Features.” 2011. Masters Thesis, Wright State University. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1316025164.

MLA Handbook (7th Edition):

Crossen, Samantha Lokelani. “Investigation of Variability in Cognitive State Assessment based on Electroencephalogram-derived Features.” 2011. Web. 17 Nov 2019.

Vancouver:

Crossen SL. Investigation of Variability in Cognitive State Assessment based on Electroencephalogram-derived Features. [Internet] [Masters thesis]. Wright State University; 2011. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1316025164.

Council of Science Editors:

Crossen SL. Investigation of Variability in Cognitive State Assessment based on Electroencephalogram-derived Features. [Masters Thesis]. Wright State University; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1316025164


Linköping University

9. Westell, Jesper. Multi-Task Learning using Road Surface Condition Classification and Road Scene Semantic Segmentation.

Degree: Biomedical Engineering, 2019, Linköping University

  Understanding road surface conditions is an important component in active vehicle safety. Estimations can be achieved through image classification using increasingly popular convolutional neural networks (CNNs).… (more)

Subjects/Keywords: Computer Vision; Deep Learning; Machine Learning; Convolutional Neural Networks; Classification; Semantic Segmentation; Signal Processing; Signalbehandling

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APA (6th Edition):

Westell, J. (2019). Multi-Task Learning using Road Surface Condition Classification and Road Scene Semantic Segmentation. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157403

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Westell, Jesper. “Multi-Task Learning using Road Surface Condition Classification and Road Scene Semantic Segmentation.” 2019. Thesis, Linköping University. Accessed November 17, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157403.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Westell, Jesper. “Multi-Task Learning using Road Surface Condition Classification and Road Scene Semantic Segmentation.” 2019. Web. 17 Nov 2019.

Vancouver:

Westell J. Multi-Task Learning using Road Surface Condition Classification and Road Scene Semantic Segmentation. [Internet] [Thesis]. Linköping University; 2019. [cited 2019 Nov 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157403.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Westell J. Multi-Task Learning using Road Surface Condition Classification and Road Scene Semantic Segmentation. [Thesis]. Linköping University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157403

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Purdue University

10. Du, Yuezhi. Signal enhancement and data mining for biological and chemical samples using mass spectrometry.

Degree: PhD, Biomedical Engineering, 2015, Purdue University

 Mass spectrometry has been actively involved in the areas of healthcare, pharmaceutics, environmental analysis, food industry and forensics due to its ability to provide molecular… (more)

Subjects/Keywords: Biomarker identification; Data mining; Mass spectrometry; Sample classification; Signal enhancement; Signal processing

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APA (6th Edition):

Du, Y. (2015). Signal enhancement and data mining for biological and chemical samples using mass spectrometry. (Doctoral Dissertation). Purdue University. Retrieved from https://docs.lib.purdue.edu/open_access_dissertations/1110

Chicago Manual of Style (16th Edition):

Du, Yuezhi. “Signal enhancement and data mining for biological and chemical samples using mass spectrometry.” 2015. Doctoral Dissertation, Purdue University. Accessed November 17, 2019. https://docs.lib.purdue.edu/open_access_dissertations/1110.

MLA Handbook (7th Edition):

Du, Yuezhi. “Signal enhancement and data mining for biological and chemical samples using mass spectrometry.” 2015. Web. 17 Nov 2019.

Vancouver:

Du Y. Signal enhancement and data mining for biological and chemical samples using mass spectrometry. [Internet] [Doctoral dissertation]. Purdue University; 2015. [cited 2019 Nov 17]. Available from: https://docs.lib.purdue.edu/open_access_dissertations/1110.

Council of Science Editors:

Du Y. Signal enhancement and data mining for biological and chemical samples using mass spectrometry. [Doctoral Dissertation]. Purdue University; 2015. Available from: https://docs.lib.purdue.edu/open_access_dissertations/1110


Virginia Commonwealth University

11. Huang, Dandan. Electroencephalography (EEG)-based brain computer interfaces for rehabilitation.

Degree: PhD, Biomedical Engineering, 2012, Virginia Commonwealth University

 Objective: Brain-computer interface (BCI) technologies have been the subject of study for the past decades to help restore functions for people with severe motor disabilities… (more)

Subjects/Keywords: Brain-computer interface; Electroencephalography; Wheelchair control; Classification; Machine learning; Hybrid; Rehabilitation; Biomedical Engineering and Bioengineering; Engineering

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APA (6th Edition):

Huang, D. (2012). Electroencephalography (EEG)-based brain computer interfaces for rehabilitation. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/2761

Chicago Manual of Style (16th Edition):

Huang, Dandan. “Electroencephalography (EEG)-based brain computer interfaces for rehabilitation.” 2012. Doctoral Dissertation, Virginia Commonwealth University. Accessed November 17, 2019. https://scholarscompass.vcu.edu/etd/2761.

MLA Handbook (7th Edition):

Huang, Dandan. “Electroencephalography (EEG)-based brain computer interfaces for rehabilitation.” 2012. Web. 17 Nov 2019.

Vancouver:

Huang D. Electroencephalography (EEG)-based brain computer interfaces for rehabilitation. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2012. [cited 2019 Nov 17]. Available from: https://scholarscompass.vcu.edu/etd/2761.

Council of Science Editors:

Huang D. Electroencephalography (EEG)-based brain computer interfaces for rehabilitation. [Doctoral Dissertation]. Virginia Commonwealth University; 2012. Available from: https://scholarscompass.vcu.edu/etd/2761


The Ohio State University

12. Ghosh Dastidar, Samanwoy. Models of EEG data mining and classification in temporal lobe epilepsy: wavelet-chaos-neural network methodology and spiking neural networks.

Degree: PhD, Biomedical Engineering, 2007, The Ohio State University

 A multi-paradigm approach integrating three novel computational paradigms: wavelet transforms, chaos theory, and artificial neural networks is developed for EEG-based epilepsy diagnosis and seizure detection.… (more)

Subjects/Keywords: Temporal Lobe Epilepsy; Electroencephalogram (EEG); EEG Classification; Epilepsy Diagnosis; Seizure Detection; Wavelet Transform; Chaos Theory; Artificial Neural Networks; Spiking Neural Networks; Principal Component Analysis; Cosine Radial Basis Function

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APA (6th Edition):

Ghosh Dastidar, S. (2007). Models of EEG data mining and classification in temporal lobe epilepsy: wavelet-chaos-neural network methodology and spiking neural networks. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1180459585

Chicago Manual of Style (16th Edition):

Ghosh Dastidar, Samanwoy. “Models of EEG data mining and classification in temporal lobe epilepsy: wavelet-chaos-neural network methodology and spiking neural networks.” 2007. Doctoral Dissertation, The Ohio State University. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1180459585.

MLA Handbook (7th Edition):

Ghosh Dastidar, Samanwoy. “Models of EEG data mining and classification in temporal lobe epilepsy: wavelet-chaos-neural network methodology and spiking neural networks.” 2007. Web. 17 Nov 2019.

Vancouver:

Ghosh Dastidar S. Models of EEG data mining and classification in temporal lobe epilepsy: wavelet-chaos-neural network methodology and spiking neural networks. [Internet] [Doctoral dissertation]. The Ohio State University; 2007. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1180459585.

Council of Science Editors:

Ghosh Dastidar S. Models of EEG data mining and classification in temporal lobe epilepsy: wavelet-chaos-neural network methodology and spiking neural networks. [Doctoral Dissertation]. The Ohio State University; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1180459585


The Ohio State University

13. Ortiz-Rosario, Alexis. Improved Methodologies for the Simultanoeus Study of Two Motor Systems: Reticulospinal and Corticospinal Cooperation and Competition for Motor Control.

Degree: PhD, Biomedical Engineering, 2016, The Ohio State University

 The aim of this dissertation is to study methodologies and approaches used to enhance the understanding of how the corticospinal and reticulospinal systems cooperate and… (more)

Subjects/Keywords: Biomedical Engineering; Computer Science; Neurosciences; reticulospina system, corticospinal system, signal processing, multiple signal classification, wavelet transform, gaussian mixture model, stimulus trains, principal component analsys

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APA (6th Edition):

Ortiz-Rosario, A. (2016). Improved Methodologies for the Simultanoeus Study of Two Motor Systems: Reticulospinal and Corticospinal Cooperation and Competition for Motor Control. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1468886309

Chicago Manual of Style (16th Edition):

Ortiz-Rosario, Alexis. “Improved Methodologies for the Simultanoeus Study of Two Motor Systems: Reticulospinal and Corticospinal Cooperation and Competition for Motor Control.” 2016. Doctoral Dissertation, The Ohio State University. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468886309.

MLA Handbook (7th Edition):

Ortiz-Rosario, Alexis. “Improved Methodologies for the Simultanoeus Study of Two Motor Systems: Reticulospinal and Corticospinal Cooperation and Competition for Motor Control.” 2016. Web. 17 Nov 2019.

Vancouver:

Ortiz-Rosario A. Improved Methodologies for the Simultanoeus Study of Two Motor Systems: Reticulospinal and Corticospinal Cooperation and Competition for Motor Control. [Internet] [Doctoral dissertation]. The Ohio State University; 2016. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1468886309.

Council of Science Editors:

Ortiz-Rosario A. Improved Methodologies for the Simultanoeus Study of Two Motor Systems: Reticulospinal and Corticospinal Cooperation and Competition for Motor Control. [Doctoral Dissertation]. The Ohio State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1468886309

14. Mostaco-Guidolin, Leila Buttner. Multimodal characterization of atherosclerotic cardiovascular disease with label-free non-linear optical imaging techniques.

Degree: Biomedical Engineering, 2010, University of Manitoba

 Application of the nonlinear optical microscopy (NLOM) for investigation of biological samples has, to date, primarily focused upon the qualitative analysis of images. The general… (more)

Subjects/Keywords: nonlienar optics; atherosclerosis; shg; cars; tpef; texture analysis; classification; multiphoton

…standard deviation. (© L.Mosta¸co-Guidolin, 2014) . . . . . . . . Classification of… …Summary of the SVM classification results obtained considering the OIPB and textural features… …39 81 85 86 Summary of the nonlinear SVM classification for collagen SHG images… …parameters. 103 Summary of the nonlinear SVM classification percentual accuracy for CARS images… …113 Overall classification results obtained for CARS images separated considering… 

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APA (6th Edition):

Mostaco-Guidolin, L. B. (2010). Multimodal characterization of atherosclerotic cardiovascular disease with label-free non-linear optical imaging techniques. (Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/30569

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mostaco-Guidolin, Leila Buttner. “Multimodal characterization of atherosclerotic cardiovascular disease with label-free non-linear optical imaging techniques.” 2010. Thesis, University of Manitoba. Accessed November 17, 2019. http://hdl.handle.net/1993/30569.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mostaco-Guidolin, Leila Buttner. “Multimodal characterization of atherosclerotic cardiovascular disease with label-free non-linear optical imaging techniques.” 2010. Web. 17 Nov 2019.

Vancouver:

Mostaco-Guidolin LB. Multimodal characterization of atherosclerotic cardiovascular disease with label-free non-linear optical imaging techniques. [Internet] [Thesis]. University of Manitoba; 2010. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1993/30569.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mostaco-Guidolin LB. Multimodal characterization of atherosclerotic cardiovascular disease with label-free non-linear optical imaging techniques. [Thesis]. University of Manitoba; 2010. Available from: http://hdl.handle.net/1993/30569

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Linköping University

15. Johansson, Philip. Incremental Learning of Deep Convolutional Neural Networks for Tumour Classification in Pathology Images.

Degree: Biomedical Engineering, 2019, Linköping University

  Medical doctors understaffing is becoming a compelling problem in many healthcare systems. This problem can be alleviated by utilising Computer-Aided Diagnosis (CAD) systems to… (more)

Subjects/Keywords: Deep Learning; Convolutional Nerual Networks; Pathology; Incremental Learning; Catastrophic Forgetting; Generative Adversarial Networks; Auxiliary Classification Generative Adversarial Networks; Computer Sciences; Datavetenskap (datalogi); Medical Image Processing; Medicinsk bildbehandling

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APA (6th Edition):

Johansson, P. (2019). Incremental Learning of Deep Convolutional Neural Networks for Tumour Classification in Pathology Images. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158225

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Johansson, Philip. “Incremental Learning of Deep Convolutional Neural Networks for Tumour Classification in Pathology Images.” 2019. Thesis, Linköping University. Accessed November 17, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158225.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Johansson, Philip. “Incremental Learning of Deep Convolutional Neural Networks for Tumour Classification in Pathology Images.” 2019. Web. 17 Nov 2019.

Vancouver:

Johansson P. Incremental Learning of Deep Convolutional Neural Networks for Tumour Classification in Pathology Images. [Internet] [Thesis]. Linköping University; 2019. [cited 2019 Nov 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158225.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Johansson P. Incremental Learning of Deep Convolutional Neural Networks for Tumour Classification in Pathology Images. [Thesis]. Linköping University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158225

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Iowa

16. De Ryk, Jessica Corinne. Lung cancer: an evaluation of volumetric histopathological architecture with correlation to computed tomography.

Degree: PhD, Biomedical Engineering, 2008, University of Iowa

  Over 190,000 Americans die every year from lung cancer, making it the number one cause of death from cancer in America. Lung cancer has… (more)

Subjects/Keywords: biomass; classification; computed tomography; heterogeneity; immunohistochemistry; lung cancer; Biomedical Engineering and Bioengineering

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APA (6th Edition):

De Ryk, J. C. (2008). Lung cancer: an evaluation of volumetric histopathological architecture with correlation to computed tomography. (Doctoral Dissertation). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/201

Chicago Manual of Style (16th Edition):

De Ryk, Jessica Corinne. “Lung cancer: an evaluation of volumetric histopathological architecture with correlation to computed tomography.” 2008. Doctoral Dissertation, University of Iowa. Accessed November 17, 2019. https://ir.uiowa.edu/etd/201.

MLA Handbook (7th Edition):

De Ryk, Jessica Corinne. “Lung cancer: an evaluation of volumetric histopathological architecture with correlation to computed tomography.” 2008. Web. 17 Nov 2019.

Vancouver:

De Ryk JC. Lung cancer: an evaluation of volumetric histopathological architecture with correlation to computed tomography. [Internet] [Doctoral dissertation]. University of Iowa; 2008. [cited 2019 Nov 17]. Available from: https://ir.uiowa.edu/etd/201.

Council of Science Editors:

De Ryk JC. Lung cancer: an evaluation of volumetric histopathological architecture with correlation to computed tomography. [Doctoral Dissertation]. University of Iowa; 2008. Available from: https://ir.uiowa.edu/etd/201


Case Western Reserve University

17. Salvado, Olivier. CHARACTERIZATION OF ATHEROSCLEROSIS WITH MAGNETIC RESONANCE IMAGING, CHALLENGES AND VALIDATION.

Degree: PhD, Biomedical Engineering, 2006, Case Western Reserve University

 The long-term goal of this research is the characterization of atherosclerosis lesions in vivo using Magnetic Resonance Imaging (MRI). Our particular interest is the computer-aided… (more)

Subjects/Keywords: Engineering, Biomedical; Atheroclerosis; Magnetic Resonance Imaging; Intensity inhomegeneity; Partial volume effect; Noise; Anisotropic diffusion; Vulnerable plaque; Cryoimaging; Segmetnation; Tissue classification; Registration

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APA (6th Edition):

Salvado, O. (2006). CHARACTERIZATION OF ATHEROSCLEROSIS WITH MAGNETIC RESONANCE IMAGING, CHALLENGES AND VALIDATION. (Doctoral Dissertation). Case Western Reserve University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1152214735

Chicago Manual of Style (16th Edition):

Salvado, Olivier. “CHARACTERIZATION OF ATHEROSCLEROSIS WITH MAGNETIC RESONANCE IMAGING, CHALLENGES AND VALIDATION.” 2006. Doctoral Dissertation, Case Western Reserve University. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1152214735.

MLA Handbook (7th Edition):

Salvado, Olivier. “CHARACTERIZATION OF ATHEROSCLEROSIS WITH MAGNETIC RESONANCE IMAGING, CHALLENGES AND VALIDATION.” 2006. Web. 17 Nov 2019.

Vancouver:

Salvado O. CHARACTERIZATION OF ATHEROSCLEROSIS WITH MAGNETIC RESONANCE IMAGING, CHALLENGES AND VALIDATION. [Internet] [Doctoral dissertation]. Case Western Reserve University; 2006. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1152214735.

Council of Science Editors:

Salvado O. CHARACTERIZATION OF ATHEROSCLEROSIS WITH MAGNETIC RESONANCE IMAGING, CHALLENGES AND VALIDATION. [Doctoral Dissertation]. Case Western Reserve University; 2006. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1152214735


University of Southern California

18. Fishel, Jeremy A. Design and use of a biomimetic tactile microvibration sensor with human-like sensitivity and its application in texture discrimination using Bayesian exploration.

Degree: PhD, Biomedical Engineering, 2012, University of Southern California

 The cutaneous sensing of microvibrations in human fingertips plays a central role in the detection of slip-related and dynamic information critical for tool usage, reflexive… (more)

Subjects/Keywords: tactile sensing; tactile sensor; biomimetic; BioTac; microvibration; vibration; touch; Pacinian corpuscle; fluid-filled sensor; Bayesian exploration; texture discrimination; human performance; impact; robot; artificial texture discrimination; object identification; Bayesian inference; machine learning; classification

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APA (6th Edition):

Fishel, J. A. (2012). Design and use of a biomimetic tactile microvibration sensor with human-like sensitivity and its application in texture discrimination using Bayesian exploration. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/47124/rec/1863

Chicago Manual of Style (16th Edition):

Fishel, Jeremy A. “Design and use of a biomimetic tactile microvibration sensor with human-like sensitivity and its application in texture discrimination using Bayesian exploration.” 2012. Doctoral Dissertation, University of Southern California. Accessed November 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/47124/rec/1863.

MLA Handbook (7th Edition):

Fishel, Jeremy A. “Design and use of a biomimetic tactile microvibration sensor with human-like sensitivity and its application in texture discrimination using Bayesian exploration.” 2012. Web. 17 Nov 2019.

Vancouver:

Fishel JA. Design and use of a biomimetic tactile microvibration sensor with human-like sensitivity and its application in texture discrimination using Bayesian exploration. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Nov 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/47124/rec/1863.

Council of Science Editors:

Fishel JA. Design and use of a biomimetic tactile microvibration sensor with human-like sensitivity and its application in texture discrimination using Bayesian exploration. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/47124/rec/1863

19. Deshpande, Aditi. Mufti-Dimensional Polarimetric Pattern Recognition & Classification Techniques for Immunohistochemical Imaging of Cancer.

Degree: MSin Engineering, Biomedical Engineering, 2014, University of Akron

 The most important step in treating cancer is an accurate early diagnosis and proper surgical removal. In the first part of this study, statistical data… (more)

Subjects/Keywords: Biomedical Engineering; Medical Imaging; imaging, image processing, imaging of tumor margins, cancer classification, pattern recognition

…21 2. The KNN classification algorithm… …after classification .....................................70 11. Plot of diattenuation data… …points after classification .......................................70 12. Plot of total… …retardance data points after classification ...................................71 13. Cluster plot… …marrow, etc. In this work, lung cancer samples have been used to design classification and… 

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APA (6th Edition):

Deshpande, A. (2014). Mufti-Dimensional Polarimetric Pattern Recognition & Classification Techniques for Immunohistochemical Imaging of Cancer. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1399573035

Chicago Manual of Style (16th Edition):

Deshpande, Aditi. “Mufti-Dimensional Polarimetric Pattern Recognition & Classification Techniques for Immunohistochemical Imaging of Cancer.” 2014. Masters Thesis, University of Akron. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1399573035.

MLA Handbook (7th Edition):

Deshpande, Aditi. “Mufti-Dimensional Polarimetric Pattern Recognition & Classification Techniques for Immunohistochemical Imaging of Cancer.” 2014. Web. 17 Nov 2019.

Vancouver:

Deshpande A. Mufti-Dimensional Polarimetric Pattern Recognition & Classification Techniques for Immunohistochemical Imaging of Cancer. [Internet] [Masters thesis]. University of Akron; 2014. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1399573035.

Council of Science Editors:

Deshpande A. Mufti-Dimensional Polarimetric Pattern Recognition & Classification Techniques for Immunohistochemical Imaging of Cancer. [Masters Thesis]. University of Akron; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1399573035


University of Florida

20. Opri, Enrico. Multivariate Pattern Decoding of fMRI Signals in Disorders of Consciousness.

Degree: MS, Biomedical Engineering, 2014, University of Florida

Subjects/Keywords: Datasets; Magnetic resonance imaging; Mental imagery; Pain perception; Paradigms; Persistent vegetative states; Preprocessing; Searchlights; Signals; Toolboxes; classification; doc; fmri

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APA (6th Edition):

Opri, E. (2014). Multivariate Pattern Decoding of fMRI Signals in Disorders of Consciousness. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0047260

Chicago Manual of Style (16th Edition):

Opri, Enrico. “Multivariate Pattern Decoding of fMRI Signals in Disorders of Consciousness.” 2014. Masters Thesis, University of Florida. Accessed November 17, 2019. http://ufdc.ufl.edu/UFE0047260.

MLA Handbook (7th Edition):

Opri, Enrico. “Multivariate Pattern Decoding of fMRI Signals in Disorders of Consciousness.” 2014. Web. 17 Nov 2019.

Vancouver:

Opri E. Multivariate Pattern Decoding of fMRI Signals in Disorders of Consciousness. [Internet] [Masters thesis]. University of Florida; 2014. [cited 2019 Nov 17]. Available from: http://ufdc.ufl.edu/UFE0047260.

Council of Science Editors:

Opri E. Multivariate Pattern Decoding of fMRI Signals in Disorders of Consciousness. [Masters Thesis]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0047260

21. Bodduluri, Sandeep. Analysis of chronic obstructive pulmonary disease (COPD) using CT images.

Degree: MS, Biomedical Engineering, 2012, University of Iowa

  Chronic Obstructive Pulmonary Disease (COPD), a growing health concern, is the fourth leading cause of death in the United States. While people habituated to… (more)

Subjects/Keywords: classification; CT COPD; density texture; images; jacobian; Biomedical Engineering and Bioengineering

…26 3.7. Classification (KNN classifier)… …31 4.2. Classification… …vs. Non-COPD (Lobar Level) .......45 4.2.4. GOLD Category Classification (… …Whole Lung) ..................50 4.2.5. GOLD Category Classification (Lobar Level… …38 Table 8: Optimal set of features selected for severe vs. normal classification where ADI… 

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APA (6th Edition):

Bodduluri, S. (2012). Analysis of chronic obstructive pulmonary disease (COPD) using CT images. (Masters Thesis). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/2441

Chicago Manual of Style (16th Edition):

Bodduluri, Sandeep. “Analysis of chronic obstructive pulmonary disease (COPD) using CT images.” 2012. Masters Thesis, University of Iowa. Accessed November 17, 2019. https://ir.uiowa.edu/etd/2441.

MLA Handbook (7th Edition):

Bodduluri, Sandeep. “Analysis of chronic obstructive pulmonary disease (COPD) using CT images.” 2012. Web. 17 Nov 2019.

Vancouver:

Bodduluri S. Analysis of chronic obstructive pulmonary disease (COPD) using CT images. [Internet] [Masters thesis]. University of Iowa; 2012. [cited 2019 Nov 17]. Available from: https://ir.uiowa.edu/etd/2441.

Council of Science Editors:

Bodduluri S. Analysis of chronic obstructive pulmonary disease (COPD) using CT images. [Masters Thesis]. University of Iowa; 2012. Available from: https://ir.uiowa.edu/etd/2441

22. Harrivel, Angela Rose. Monitoring Attentional State with Functional Near Infrared Spectroscopy.

Degree: PhD, Biomedical Engineering, 2014, University of Michigan

 Functional Near Infrared Spectroscopy (fNIRS) is a technique for quantifying hemodynamic activity in the brain. Its portability allows application in real world operational contexts. The… (more)

Subjects/Keywords: Near Infra-red Spectroscopy; Default Mode Network; Classification; Attention; Biomedical Engineering; Engineering

Classification accuracy for study part one fNIRS data 46 9. Two across-region fNIRS time traces 47… …10. Classification accuracy for study part one fMRI data 51 11. Head probes used to… …101 36. RWCC between the two fMRI classification input features in the significant case… …varying c and g each across 8 orders of magnitude 116 D. Correlation vs. classification… …Linear Classification 128 J. Receiver Operator Characteristic plots for fMRI Results 131 K… 

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APA (6th Edition):

Harrivel, A. R. (2014). Monitoring Attentional State with Functional Near Infrared Spectroscopy. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/108861

Chicago Manual of Style (16th Edition):

Harrivel, Angela Rose. “Monitoring Attentional State with Functional Near Infrared Spectroscopy.” 2014. Doctoral Dissertation, University of Michigan. Accessed November 17, 2019. http://hdl.handle.net/2027.42/108861.

MLA Handbook (7th Edition):

Harrivel, Angela Rose. “Monitoring Attentional State with Functional Near Infrared Spectroscopy.” 2014. Web. 17 Nov 2019.

Vancouver:

Harrivel AR. Monitoring Attentional State with Functional Near Infrared Spectroscopy. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/2027.42/108861.

Council of Science Editors:

Harrivel AR. Monitoring Attentional State with Functional Near Infrared Spectroscopy. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/108861


University of Michigan

23. Way, Ted Win. Computer-aided Diagnosis of Pulmonary Nodules in Thoracic Computed Tomography.

Degree: PhD, Biomedical Engineering, 2008, University of Michigan

 Lung cancer is the leading cause of cancer death in the United States. The five-year survival rate is 15% because most patients present with advanced… (more)

Subjects/Keywords: Computer-aided Diagnosis; Computed Tomography; Segmentation; Classification; Pulmonary Nodule; Machine Learning; Biomedical Engineering; Computer Science; Electrical Engineering; Engineering

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APA (6th Edition):

Way, T. W. (2008). Computer-aided Diagnosis of Pulmonary Nodules in Thoracic Computed Tomography. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/60814

Chicago Manual of Style (16th Edition):

Way, Ted Win. “Computer-aided Diagnosis of Pulmonary Nodules in Thoracic Computed Tomography.” 2008. Doctoral Dissertation, University of Michigan. Accessed November 17, 2019. http://hdl.handle.net/2027.42/60814.

MLA Handbook (7th Edition):

Way, Ted Win. “Computer-aided Diagnosis of Pulmonary Nodules in Thoracic Computed Tomography.” 2008. Web. 17 Nov 2019.

Vancouver:

Way TW. Computer-aided Diagnosis of Pulmonary Nodules in Thoracic Computed Tomography. [Internet] [Doctoral dissertation]. University of Michigan; 2008. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/2027.42/60814.

Council of Science Editors:

Way TW. Computer-aided Diagnosis of Pulmonary Nodules in Thoracic Computed Tomography. [Doctoral Dissertation]. University of Michigan; 2008. Available from: http://hdl.handle.net/2027.42/60814

24. Kostick, Nathan H. Novel Carbon-Nanotube Based Neural Interface for Chronic Recording of Glossopharyngeal Nerve Activity.

Degree: MSs (Engineering), Biomedical Engineering, 2018, Case Western Reserve University School of Graduate Studies

 Neural recordings have been used to study physiology since the early1900’s. However, high quality recordings of small autonomic nerves have been limitedto acute studies as… (more)

Subjects/Keywords: Biomedical Engineering; Neural Engineering, Carbon Nano-Tube, Peripheral Nervous System, CNT, CNTY, PNS, Neural Recording, Biomedical Engineering, Neural Interface, Carbon Nano-Tube Yarn, Chronic Recording, GPN, CSN, Glossopharyngeal Nerve, Spike Sorting, Neural Classification

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APA (6th Edition):

Kostick, N. H. (2018). Novel Carbon-Nanotube Based Neural Interface for Chronic Recording of Glossopharyngeal Nerve Activity. (Masters Thesis). Case Western Reserve University School of Graduate Studies. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1517920588275806

Chicago Manual of Style (16th Edition):

Kostick, Nathan H. “Novel Carbon-Nanotube Based Neural Interface for Chronic Recording of Glossopharyngeal Nerve Activity.” 2018. Masters Thesis, Case Western Reserve University School of Graduate Studies. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1517920588275806.

MLA Handbook (7th Edition):

Kostick, Nathan H. “Novel Carbon-Nanotube Based Neural Interface for Chronic Recording of Glossopharyngeal Nerve Activity.” 2018. Web. 17 Nov 2019.

Vancouver:

Kostick NH. Novel Carbon-Nanotube Based Neural Interface for Chronic Recording of Glossopharyngeal Nerve Activity. [Internet] [Masters thesis]. Case Western Reserve University School of Graduate Studies; 2018. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1517920588275806.

Council of Science Editors:

Kostick NH. Novel Carbon-Nanotube Based Neural Interface for Chronic Recording of Glossopharyngeal Nerve Activity. [Masters Thesis]. Case Western Reserve University School of Graduate Studies; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1517920588275806

25. De Hoedt, Amanda Marie. Clubfoot Image Classification.

Degree: MS, Biomedical Engineering, 2013, University of Iowa

  Clubfoot is a congenital foot disorder that, left untreated, can limit a person's mobility by making it difficult and painful to walk. Although inexpensive… (more)

Subjects/Keywords: Classification; Clubfoot; Developing World; Machine Learning; Point-of-care; Talipes; Biomedical Engineering and Bioengineering

…Table 17: Three majority classifiers were used in the Quality on Quality classification… …classification scheme to predict an image’s orientation given a PHOW feature vector that was generated… …Table 19: Three SMO classifiers were used in the Quality on Quality classification scheme to… …37 Table 20: Naïve Bayes classifiers were used in the quality-based classification… …39 Table 21: SMO classifiers were used in the quality-based classification scheme to… 

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APA (6th Edition):

De Hoedt, A. M. (2013). Clubfoot Image Classification. (Masters Thesis). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/4836

Chicago Manual of Style (16th Edition):

De Hoedt, Amanda Marie. “Clubfoot Image Classification.” 2013. Masters Thesis, University of Iowa. Accessed November 17, 2019. https://ir.uiowa.edu/etd/4836.

MLA Handbook (7th Edition):

De Hoedt, Amanda Marie. “Clubfoot Image Classification.” 2013. Web. 17 Nov 2019.

Vancouver:

De Hoedt AM. Clubfoot Image Classification. [Internet] [Masters thesis]. University of Iowa; 2013. [cited 2019 Nov 17]. Available from: https://ir.uiowa.edu/etd/4836.

Council of Science Editors:

De Hoedt AM. Clubfoot Image Classification. [Masters Thesis]. University of Iowa; 2013. Available from: https://ir.uiowa.edu/etd/4836

26. Metzger, Andrew. An automated tissue classification pipeline for magnetic resonance images of infant brains using age-specific atlases and level set segmentation.

Degree: MS, Biomedical Engineering, 2016, University of Iowa

  Quantifying tissue volumes in pediatric brains from magnetic resonance (MR) images can provide insight into etiology and onset of neurological disease. Unbiased volumetric analysis… (more)

Subjects/Keywords: publicabstract; atlas-based segmentation; automated pipeline; Image Processing; level set segmentation; Magnetic Resonance images; tissue classification; Biomedical Engineering and Bioengineering

…collection of prior knowledge that is used in tissue classification. Because of the fast growth of… …classification in an additional post-processing step. v TABLE OF CONTENTS LIST OF TABLES… …1 1.2.1 Modern Approaches in Tissue Classification… …15 2.2.3 Tissue Classification… …21 Figure 6: Final classification results of a typical subject using the one-year-old atlas… 

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APA (6th Edition):

Metzger, A. (2016). An automated tissue classification pipeline for magnetic resonance images of infant brains using age-specific atlases and level set segmentation. (Masters Thesis). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/3143

Chicago Manual of Style (16th Edition):

Metzger, Andrew. “An automated tissue classification pipeline for magnetic resonance images of infant brains using age-specific atlases and level set segmentation.” 2016. Masters Thesis, University of Iowa. Accessed November 17, 2019. https://ir.uiowa.edu/etd/3143.

MLA Handbook (7th Edition):

Metzger, Andrew. “An automated tissue classification pipeline for magnetic resonance images of infant brains using age-specific atlases and level set segmentation.” 2016. Web. 17 Nov 2019.

Vancouver:

Metzger A. An automated tissue classification pipeline for magnetic resonance images of infant brains using age-specific atlases and level set segmentation. [Internet] [Masters thesis]. University of Iowa; 2016. [cited 2019 Nov 17]. Available from: https://ir.uiowa.edu/etd/3143.

Council of Science Editors:

Metzger A. An automated tissue classification pipeline for magnetic resonance images of infant brains using age-specific atlases and level set segmentation. [Masters Thesis]. University of Iowa; 2016. Available from: https://ir.uiowa.edu/etd/3143

27. Hamilton, Erin Kinzel. Multiscale and meta-analytic approaches to inference in clinical healthcare data.

Degree: PhD, Biomedical Engineering, 2013, Georgia Tech

 The field of medicine is regularly faced with the challenge of utilizing information that is complicated or difficult to characterize. Physicians often must use their… (more)

Subjects/Keywords: Rasch model; Bayesian hierarchical model; Paired data; Meta-analysis; Heterogeneity; Scale-mixing wavelet transform; Sampling distribution; Bootstrapping; Dental sealants; Waveletes; Spectral tools; Breast cancer; Scaling; Wavelet spectra; Weighted regression; Theil; Microcalcification; Diagnostic classification; Image enhancement; Rasch models; Item response theory; Sampling (Statistics); Bootstrap (Statistics)

…44 18 Results of classification by logistic regression using Hd . . . . . . . . . . 48… …19 Results of classification by logistic regression using (Hd , Hh )… …49 20 Results of classification by logistic regression using (Hd , Hv , Hh )… …50 21 Results of linear and quadratic classification based on pair (Hd , Hh )… …Binary Classification Outcomes . . . . . . . . . . . . . . . . . . . . . . . 86 17 ix LIST… 

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APA (6th Edition):

Hamilton, E. K. (2013). Multiscale and meta-analytic approaches to inference in clinical healthcare data. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47600

Chicago Manual of Style (16th Edition):

Hamilton, Erin Kinzel. “Multiscale and meta-analytic approaches to inference in clinical healthcare data.” 2013. Doctoral Dissertation, Georgia Tech. Accessed November 17, 2019. http://hdl.handle.net/1853/47600.

MLA Handbook (7th Edition):

Hamilton, Erin Kinzel. “Multiscale and meta-analytic approaches to inference in clinical healthcare data.” 2013. Web. 17 Nov 2019.

Vancouver:

Hamilton EK. Multiscale and meta-analytic approaches to inference in clinical healthcare data. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1853/47600.

Council of Science Editors:

Hamilton EK. Multiscale and meta-analytic approaches to inference in clinical healthcare data. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47600

.