A three in one bottom-up framework for simultaneous semantic segmentation, instance segmentation and classification of multi-organ nuclei in digital cancer histology-Reference-Cited by-同舟云学术

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A three in one bottom-up framework for simultaneous semantic segmentation, instance segmentation and classification of multi-organ nuclei in digital cancer histology

Published:2024-06 Issue: Volume:146 Page:105047
ISSN:0262-8856
Container-title:Image and Vision Computing
language:en
Short-container-title:Image and Vision Computing

Author:

Ahmad Ibtihaj,Israr Syed Muhammad,Islam Zain Ul

Publisher

Elsevier BV

Reference41 articles.

1. Dilated residual grooming kernel model for breast cancer detection;Kashyap;Pattern Recogn. Lett.,2022

2. Nuclear shape and orientation features from h&e images predict survival in early-stage estrogen receptor-positive breast cancers;Lu;Lab. Investig.,2018

3. Detecting cancer metastases on gigapixel pathology images;Liu,2017

4. A bottom-up approach for tumour differentiation in whole slide images of lung adenocarcinoma;Alsubaie,2018

5. Pointnu-net: simultaneous multi-tissue histology nuclei segmentation and classification in the clinical wild;Yao;IEEE transactions on emerging topics, Comput. Intell.,2024

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