Detection and Classification of Psoriasis in Histopathology Images.

Date of Submission

December 2015

Date of Award

Winter 12-12-2016

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science

Department

Computer Vision and Pattern Recognition Unit (CVPR-Kolkata)

Supervisor

Garain, Utpal (CVPR-Kolkata; ISI)

Abstract (Summary of the Work)

Recent advances in imaging techniques has lead better visual representation of the internals of our body for clinical analysis and medical intervention, however the task is tedious and subject to interpreter variability. An automated quantitative analysis of the images would not only relieve us of the human effort, but considerably reduce the inaccuracies involved. The current work explores the techniques of image processing and analysis to extract vital information out of psoriasis histopathology images, and discuss a method of classifying these into diseased or non diseased classes.

Comments

ProQuest Collection ID: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:28843203

Control Number

ISI-DISS-2015-331

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI

http://dspace.isical.ac.in:8080/jspui/handle/10263/6488

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