Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

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Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images.Deep learning based tissue analysis predicts outcome in colorectal cancer.Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies

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P2860

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

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2017 nî lūn-bûn

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2017年学术文章

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name

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

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Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

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Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

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P1476

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

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P2093

Allen P Miraflor

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Andrea M Olofson

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Arief A Suriawinata

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Bruno Korbar

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Catherine M Nicka

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Lorenzo Torresani

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Matthew A Suriawinata

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Saeed Hassanpour

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P2860

Deep learning

Histopathological image analysis: a review

History of pathology: comparison of the use of the microscope in pathology in Germany and the United States during the nineteenth century.

Assisted primary screening using the automated ThinPrep Imaging System.

Image analysis and morphometry in the diagnosis of breast cancer.

Error reduction in surgical pathology.

Classification of mitotic figures with convolutional neural networks and seeded blob features

Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

Role of the serrated pathway in colorectal cancer pathogenesis.

Update on the serrated pathway to colorectal carcinoma.

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scholarly article

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10.4103/JPI.JPI_34_17

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2017-07-25T00:00:00Z

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1703.01550

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deep learning

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Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

about

P2860

P2860

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

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P1476

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P2860

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P932