June 11, 2024, 4:50 a.m. | Akash Modi, Sumit Kumar Jha, Purnendu Mishra, Rajiv Kumar, Kiran Aatre, Gursewak Singh, Shubham Mathur

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.05828v1 Announce Type: new
Abstract: Digital pathology and microscopy image analysis are widely employed in the segmentation of digitally scanned IHC slides, primarily to identify cancer and pinpoint regions of interest (ROI) indicative of tumor presence. However, current ROI segmentation models are either stain-specific or suffer from the issues of stain and scanner variance due to different staining protocols or modalities across multiple labs. Also, tissues like Ductal Carcinoma in Situ (DCIS), acini, etc. are often classified as Tumors due …

abstract analysis arxiv cancer convolutional cs.ai cs.cv current digital digital pathology eess.iv however identify image indicative microscopy network pathology roi segmentation slides type

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