Citation
Umar li, Umar Mustaqim and Ahmad Fauzi, Mohammad Faizal (2022) Breast Cancer Scoring In PR- IHC Histopathology Images Using Deep Learning Model. Periodic Research Publication, Faculty of Engineering. (Unpublished)
Text
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Abstract
Digital Pathology has proven to be very beneficial in PH-IHC scoring on breast cancer samples. This project aims to introduce the usage of machine learning in Digital Pathology to create an automated PR-IHC scoring system. Cytomine algorithm library and annotation feature has been used as the main computing platform. Cytomine is also used as the main database to store high resolution histopathology images.
Item Type: | Other |
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Uncontrolled Keywords: | Deep learning, Digital pathology, cancer |
Subjects: | R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics R Medicine > RB Pathology |
Divisions: | Faculty of Engineering (FOE) |
Depositing User: | Assoc. Dr Chee Pun Ooi |
Date Deposited: | 30 Nov 2022 04:12 |
Last Modified: | 30 Nov 2022 04:12 |
URII: | http://shdl.mmu.edu.my/id/eprint/10658 |
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