Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad

Manual screening of colorectal biopsy tissue under microscope to conform the presence of cancerous cell is difficult, arduous and time consuming. The criteria in diagnosing colorectal cancer cell are gland shape and nucleus size. In this study, we proposed a method of image pre-processing to extract...

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Main Author:	Ahmad, Mohd. Yamin
Format:	Thesis
Language:	English
Published:	2015
Subjects:	Biomedical engineering Optical data processing
Online Access:	https://ir.uitm.edu.my/id/eprint/14066/1/TM_MOHD.%20YAMIN%20AHMAD%20CS%2015_5.pdf
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id	my-uitm-ir.14066
record_format	uketd_dc
spelling	my-uitm-ir.140662022-04-18T04:41:34Z Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad 2015-01 Ahmad, Mohd. Yamin Biomedical engineering Optical data processing Manual screening of colorectal biopsy tissue under microscope to conform the presence of cancerous cell is difficult, arduous and time consuming. The criteria in diagnosing colorectal cancer cell are gland shape and nucleus size. In this study, we proposed a method of image pre-processing to extract the important feature of colorectal tissue images. Images captured under microscope may vary in colour brightness due to different H&E stain concentration and the size of biopsy tissue. To overcome this problem a method using HSV colour model to remove element outside the area of nucleus is used. A novel method named Pixel Mask Analyzer is proposed to clean the image and remove noises. Meanwhile, the gland boundary tracking and segmentation is proposed to extract the gland shape. By using the result of gland tracking, nucleus size that forms the glands are measured. By combining result of gland shapes and nucleus size, the image classification is performed. The result shows that classification achieves 96.9% accuracy by using the proposed methods. With the high accuracy results and findings of this study, it is hope that the study can contribute a very substantial amount of outcomes that would greatly benefit the research areas especially in image processing and classification of colorectal cancer. 2015-01 Thesis https://ir.uitm.edu.my/id/eprint/14066/ https://ir.uitm.edu.my/id/eprint/14066/1/TM_MOHD.%20YAMIN%20AHMAD%20CS%2015_5.pdf text en public mphil masters Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences Mohamed, Azlinah (Professor Dr.)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Mohamed, Azlinah (Professor Dr.)
topic	Biomedical engineering Optical data processing
spellingShingle	Biomedical engineering Optical data processing Ahmad, Mohd. Yamin Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad
description	Manual screening of colorectal biopsy tissue under microscope to conform the presence of cancerous cell is difficult, arduous and time consuming. The criteria in diagnosing colorectal cancer cell are gland shape and nucleus size. In this study, we proposed a method of image pre-processing to extract the important feature of colorectal tissue images. Images captured under microscope may vary in colour brightness due to different H&E stain concentration and the size of biopsy tissue. To overcome this problem a method using HSV colour model to remove element outside the area of nucleus is used. A novel method named Pixel Mask Analyzer is proposed to clean the image and remove noises. Meanwhile, the gland boundary tracking and segmentation is proposed to extract the gland shape. By using the result of gland tracking, nucleus size that forms the glands are measured. By combining result of gland shapes and nucleus size, the image classification is performed. The result shows that classification achieves 96.9% accuracy by using the proposed methods. With the high accuracy results and findings of this study, it is hope that the study can contribute a very substantial amount of outcomes that would greatly benefit the research areas especially in image processing and classification of colorectal cancer.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Ahmad, Mohd. Yamin
author_facet	Ahmad, Mohd. Yamin
author_sort	Ahmad, Mohd. Yamin
title	Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad
title_short	Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad
title_full	Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad
title_fullStr	Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad
title_full_unstemmed	Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad
title_sort	image feature extraction for colorectal cancer cells classification / mohd. yamin ahmad
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2015
url	https://ir.uitm.edu.my/id/eprint/14066/1/TM_MOHD.%20YAMIN%20AHMAD%20CS%2015_5.pdf
_version_	1783733206145564672

Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad

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