Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| Idioma: | English |
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Brac University
2022
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| Acesso em linha: | http://hdl.handle.net/10361/16671 |
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10361-166712022-05-25T21:01:42Z Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images Hossain, Mainul Haque, Shataddru Shyan Ahmed, Humayun Mahdi, Hossain Al Aich, Ankan Reza, Md Tanzim Department of Computer Science and Engineering, Brac University Colon Cancer Deep learning CNN Image classification Whole slide images Histopathological images Explainable AI Optimization algorithms LIME Artificial intelligence Cognitive learning theory (Deep learning) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 32-34). Colon cancer is one the most prominent and daunting life threatening illnesses in the world. Histopathological diagnosis is one of the most important factors in determining cancer type. The current study aims to create a computer-aided diagnosis system for differentiating tissue cells, benign colon tissues, and adenocarcinomas tissues of the colon, using convolutional neural networks and digital pathology images for such tumors. As a result, in the coming years, artificial intelligence will be a promising technology. The LC25000 dataset, which included 5000 photographs for each class, produced a total of 25000 digital images for lung and colonic cancer cells, as well as healthy cells. The photos of lung cancer were not included in our study because it was primarily focused on colon cancer. To categorize and classify the histopathological slides of adenocarcinomas and benign cells in the colon, a Convolutional neural network architecture was implemented. We also explored optimization techniques such as Explainable AI techniques, Lime and DeepLift to better understand the reasoning behind the decision the model arrived at. This allowed us to better understand and optimize our models for a more consistent accurate classification. Diagnosis validity of greater than 94% was obtained for colon distinguishing adenocarcinoma and benign colonic cells. Mainul Hossain Shataddru Shyan Haque Humayun Ahmed Hossain Al Mahdi Ankan Aich B. Computer Science 2022-05-25T05:17:07Z 2022-05-25T05:17:07Z 2022 2022-01 Thesis ID 15341003 ID 21241079 ID 17101358 ID 17201084 ID 18101445 http://hdl.handle.net/10361/16671 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 34 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Colon Cancer Deep learning CNN Image classification Whole slide images Histopathological images Explainable AI Optimization algorithms LIME Artificial intelligence Cognitive learning theory (Deep learning) |
| spellingShingle |
Colon Cancer Deep learning CNN Image classification Whole slide images Histopathological images Explainable AI Optimization algorithms LIME Artificial intelligence Cognitive learning theory (Deep learning) Hossain, Mainul Haque, Shataddru Shyan Ahmed, Humayun Mahdi, Hossain Al Aich, Ankan Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Reza, Md Tanzim |
| author_facet |
Reza, Md Tanzim Hossain, Mainul Haque, Shataddru Shyan Ahmed, Humayun Mahdi, Hossain Al Aich, Ankan |
| format |
Thesis |
| author |
Hossain, Mainul Haque, Shataddru Shyan Ahmed, Humayun Mahdi, Hossain Al Aich, Ankan |
| author_sort |
Hossain, Mainul |
| title |
Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images |
| title_short |
Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images |
| title_full |
Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images |
| title_fullStr |
Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images |
| title_full_unstemmed |
Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images |
| title_sort |
early stage detection and classification of colon cancer using deep learning and explainable ai on histopathological images |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/16671 |
| work_keys_str_mv |
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| _version_ |
1814307202755723264 |