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New Directions for Structure Segmentation, Phenotyping, and Language Interfacing in Histopathology

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New Directions for Structure Segmentation, Phenotyping, and Language Interfacing in Histopathology Progress in deep learning brings new tools and methods that start reshaping pathology practice and advancing research in oncology. As a postdoctoral researcher in the Mahmood Lab (Harvard Medical School, 2022–), I played a pivotal role in the development and evaluation of “foundation models” for pathology – general-purpose models that can be used for various downstream tasks. Despite advances, foundation models still face several key limitations that restrict their widespread adoption. First, these models are designed to provide “non-human interpretable” data representation, providing little actionable insights to practitioners. Moreover, they lack robust language interfacing capabilities, especially in providing quantitative information. Finally, they are predominantly focused on hematoxylin & eosin (H&E) staining, leaving other histopathology modalities largely untouched. In this context, I hypoth

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recordType

award

status

SIGNED

region

EU

value

1675683

unit

EUR