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:
Online Access:https://ir.uitm.edu.my/id/eprint/14066/
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author Ahmad, Mohd. Yamin
author_facet Ahmad, Mohd. Yamin
author_sort Ahmad, Mohd. Yamin
building UiTM Institutional Repository
collection Online Access
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.
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spelling uitm-140662022-04-18T04:41:34Z https://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. 2015-01 Thesis NonPeerReviewed text en https://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. (2015) Masters thesis, thesis, Universiti Teknologi MARA. <http://terminalib.uitm.edu.my/14066.pdf>
spellingShingle Biomedical engineering
Optical data processing
Ahmad, Mohd. Yamin
Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad
title 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_short Image feature extraction for colorectal cancer cells classification / Mohd. Yamin Ahmad
title_sort image feature extraction for colorectal cancer cells classification / mohd. yamin ahmad
topic Biomedical engineering
Optical data processing
url https://ir.uitm.edu.my/id/eprint/14066/