Breast Cancer Scoring In PR- IHC Histopathology Images Using Deep Learning Model

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 (Unpublished)

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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
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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