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:	http://ir.uitm.edu.my/id/eprint/14066/ http://ir.uitm.edu.my/id/eprint/14066/1/TM_MOHD.%20YAMIN%20AHMAD%20CS%2015_5.pdf

id	uitm-14066
recordtype	eprints
spelling	uitm-140662016-06-13T07:11:01Z http://ir.uitm.edu.my/id/eprint/14066/ Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad 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 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/14066/1/TM_MOHD.%20YAMIN%20AHMAD%20CS%2015_5.pdf Ahmad, Mohd. Yamin (2015) Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad. Masters thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
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
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
publishDate	2015
url	http://ir.uitm.edu.my/id/eprint/14066/ http://ir.uitm.edu.my/id/eprint/14066/1/TM_MOHD.%20YAMIN%20AHMAD%20CS%2015_5.pdf
first_indexed	2023-09-18T22:50:48Z
last_indexed	2023-09-18T22:50:48Z
_version_	1777417530489438208

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

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