Fuzzy Relevant Regions Segmentation in Breast Histopathology Images using FCM-Reference-Cited by-同舟云学术

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Fuzzy Relevant Regions Segmentation in Breast Histopathology Images using FCM

Published:2022-06-25 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)
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Author:

Hang Quah Yi¹,Jian Tan Xiao²,Ab Rahman Khairul Shakir³,Min Lu Juei¹,Hoe Teoh Leong¹,Yee Wong Chung¹,Wei Oung Qi⁴,Ling Teoh Chai¹

Affiliation:

1. Tunku Abdul Rahman University College (TARUC),Department of Electrical and Electronics Engineering,Kuala Lumpur,Malaysia

2. Tunku Abdul Rahman University College (TARUC),Centre for Multimodal Signal Processing,Department of Electrical and Electronics Engineering,Kuala Lumpur,Malaysia

3. Hospital Tuanku Fauziah,Department of Pathology,Perlis,Malaysia

4. Universiti Malaysia Perlis (UniMAP),Faculty of Electronic Engineering Technology,Perlis,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9815264/9815267/09815473.pdf?arnumber=9815473

Reference18 articles.

1. Simple Landscapes Analysis for Relevant Regions Detection in Breast Carcinoma Histopathological Images

2. Segmentation of Irrelevant Regions Using Color Thresholding Method: Application in Breast Histopathology Images;tan;Journal of Physics Conference Series,2019

3. Segmentation of Relevant Region in Breast Histopathology Images using FCM with Guided Initialization;tan;Journal of Physics Conference Series,2019

4. Automatic segmentation of whole-slide H&E stained breast histopathology images using a deep convolutional neural network architecture

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