A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology
2017 · IEEE Transactions on Medical Imaging · 1,100 citations
https://doi.org/10.1109/tmi.2017.2677499
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Ruchika Verma
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Ruchika Verma is an academic researcher from Mount Sinai Health System. The author has contributed to research in topics: Radiomics and Machine Learning in Medical Imaging & AI in cancer detection & Glioma Diagnosis and Treatment. The author has an h-index of 14, co-authored 68 publications.
ORCID: 0000-0003-4870-128XPapers by this author
worksA Multi-Organ Nucleus Segmentation Challenge
2019 · IEEE Transactions on Medical Imaging · 517 citations
https://doi.org/10.1109/tmi.2019.2947628
Federated learning enables big data for rare cancer boundary detection
2022 · Nature Communications · 313 citations
https://doi.org/10.1038/s41467-022-33407-5
A clinical benchmark of public self-supervised pathology foundation models
2025 · Nature Communications · 44 citations
https://doi.org/10.1038/s41467-025-58796-1
Detecting multiple sub-types of breast cancer in a single patient
2016 · 12 citations
https://doi.org/10.1109/icip.2016.7532839
Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge
2025 · Nature Communications · 5 citations
https://doi.org/10.1038/s41467-025-60466-1
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