Feb 18, 2021 · Abstract:High-resolution mapping of cells and tissue structures provides a foundation for developing interpretable machine-learning models ...
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May 17, 2022 · NuCLS is a large-scale multi-class dataset generated by engaging crowds of medical students and pathologists. NuCLS is sourced from the same ...
May 17, 2022 · This article describes a novel collaborative framework for engaging crowds of medical students and pathologists to produce quality labels for cell nuclei.
NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation. License. MIT license · 45 stars ...
In this paper we describe an approach for engaging crowds of medical students and pathologists that was used to produce a dataset of over 220,000 annotations of ...
NuCLS (Nucleus Classification, Localization and Segmentation) ... The NuCLS dataset contains over 220,000 labeled nuclei from breast cancer images from TCGA.
In this paper we describe an approach for engaging crowds of medical students and pathologists that was used to produce a dataset of over 220,000 annotations of ...
The NuCLS dataset contains over 220,000 labeled nuclei from breast cancer images from TCGA. · Data from both single-rater and multi-rater studies are provided.
A novel collaborative framework for engaging crowds of medical students and pathologists to produce quality labels for cell nuclei and results indicate that ...
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We explore the use of crowdsourcing for rapidly obtaining annotations for two core tasks in computational pathology: nucleus detection and nucleus segmentation.