High-resolution deep transferred ASPPU-Net for nuclei segmentation of histopathology images

Amit Kumar Chanchal; Shyam Lal; Jyoti Kini

doi:10.1007/s11548-021-02497-9

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High-resolution deep transferred ASPPU-Net for nuclei segmentation of histopathology images

Amit Kumar Chanchal Shyam Lal Jyoti Kini

Year: 2021 Journal: International Journal of Computer Assisted Radiology and Surgery Vol: 16 (12)Pages: 2159-2175 Publisher: Springer Science+Business Media

DOI: 10.1007/s11548-021-02497-9

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Keywords:

Artificial intelligence Histopathology Computer science Segmentation Deep learning Digital pathology Pattern recognition (psychology) Benchmark (surveying) Image segmentation Ground truth Pathology Medicine Cartography

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AI in cancer detection

Physical Sciences → Computer Science → Artificial Intelligence

Radiomics and Machine Learning in Medical Imaging

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Medical Imaging and Analysis

Physical Sciences → Engineering → Biomedical Engineering

High-resolution deep transferred ASPPU-Net for nuclei segmentation of histopathology images

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