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Toward explainable artificial intelligence for precision pathology
The rapid development of precision medicine in recent years has started to challenge
diagnostic pathology with respect to its ability to analyze histological images and …
diagnostic pathology with respect to its ability to analyze histological images and …
Unleashing the potential of AI for pathology: challenges and recommendations
Computational pathology is currently witnessing a surge in the development of AI
techniques, offering promise for achieving breakthroughs and significantly impacting the …
techniques, offering promise for achieving breakthroughs and significantly impacting the …
Scaling self-supervised learning for histopathology with masked image modeling
Computational pathology is revolutionizing the field of pathology by integrating advanced
computer vision and machine learning technologies into diagnostic workflows. It offers …
computer vision and machine learning technologies into diagnostic workflows. It offers …
Vim4path: Self-supervised vision mamba for histopathology images
Abstract Representation learning from Gigapixel Whole Slide Images (WSI) poses a
significant challenge in computational pathology due to the complicated nature of tissue …
significant challenge in computational pathology due to the complicated nature of tissue …
Pluto: Pathology-universal transformer
D Juyal, H Padigela, C Shah, D Shenker… - ar** computational pathology systems with artifact processing pipelines: a showcase for computation and performance trade-offs
Background Histopathology is a gold standard for cancer diagnosis. It involves extracting
tissue specimens from suspicious areas to prepare a glass slide for a microscopic …
tissue specimens from suspicious areas to prepare a glass slide for a microscopic …
Mammil: Multiple instance learning for whole slide images with state space models
Z Fang, Y Wang, Y Zhang, Z Wang… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Recently, pathological diagnosis has achieved superior performance by combining deep
learning models with the multiple instance learning (MIL) framework using whole slide …
learning models with the multiple instance learning (MIL) framework using whole slide …
[HTML][HTML] Dual attention model with reinforcement learning for classification of histology whole-slide images
Digital whole slide images (WSIs) are generally captured at microscopic resolution and
encompass extensive spatial data (several billions of pixels per image). Directly feeding …
encompass extensive spatial data (several billions of pixels per image). Directly feeding …
Computational pathology: An evolving concept
I Prassas, B Clarke, T Youssef, J Phlamon… - Clinical Chemistry and …, 2024 - degruyter.com
The initial enthusiasm about computational pathology (CP) and artificial intelligence (AI) was
that they will replace pathologists entirely on the way to fully automated diagnostics. It is …
that they will replace pathologists entirely on the way to fully automated diagnostics. It is …
A New Era in Computational Pathology: A Survey on Foundation and Vision-Language Models
Recent advances in deep learning have completely transformed the domain of
computational pathology (CPath). More specifically, it has altered the diagnostic workflow of …
computational pathology (CPath). More specifically, it has altered the diagnostic workflow of …