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Geongyu Lee

As seen in: MDPI, BioRxiv
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Articles

MurSS: A Multi-Resolution Selective Segmentation Model for Breast Cancer

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By Joonho Lee, Geongyu Lee, Tae-Yeong Kwak, Sun Woo Kim
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Open in Who Shared View Duplicates (258) Issue with article?

MurSS: Multi-resolution Selective Segmentation Model for Breast Cancer

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By Joonho Lee, Sunwoo Kim, Geongyu Lee, Tae-Yeong Kwak
| BioRxiv
Abstract We propose the Multi-resolution Selective Segmentation model (MurSS) for segmenting benign, Ductal Carcinoma In Situ, and Invasive Ductal Carcinoma in breast resection Hematoxylin and Eosin stained Whole Slide Images. MurSS simultaneously trains on context information from a wide area at low resolution and content information from a local area at high resolution, aiming for a more accurate diagnosis.
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