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

Joonho Lee¹, Geongyu Lee¹, Tae-Yeong Kwak¹, Sun Woo Kim¹, Min-Sun Jin², Chungyeul Kim³, Hyeyoon Chang¹

¹Deep Bio Inc., Seoul 08380, Republic of Korea.

²Department of Pathology, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 14647, Republic of Korea.

³Department of Pathology, Korea University Guro Hospital, Seoul 08308, Republic of Korea.

PubMed PMC DOI PDF

Abstract

Accurately segmenting cancer lesions is essential for effective personalized treatment and enhanced patient outcomes. We propose a multi-resolution selective segmentation (MurSS) model to accurately segment breast cancer lesions from hematoxylin and eosin (H&E) stained whole-slide images (WSIs). We used The Cancer Genome Atlas breast invasive carcinoma (BRCA) public dataset for training and valida…

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