Fastest Prostate Cancer Prediction on Whole-Mount Pathological Slides Using Self-Reform Multilayer Transformer

Fastest Prostate Cancer Prediction on Whole-Mount Pathological Slides Using Self-Reform Multilayer Transformer

In the clinical diagnosis of prostate cancer (PCa), the pathological image is regarded as the &#x201C;golden standard&#x201D;. Pathological images are characterized by their immense size with giga-pixel. Moreover, pixels in each whole-mount slide of PCa are increased by approximately <inl...

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Bibliographic Details
Main Authors: Linjie Xu, Xiaotian Yu, Haoming Luo, Jili Wang, Wenjie Liang, Jing Zhang, Zunlei Feng, Cheng Lu, Xiuming Zhang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Prostate cancer
pathological image
deep learning
model acceleration
Online Access:https://ieeexplore.ieee.org/document/10949171/
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https://ieeexplore.ieee.org/document/10949171/

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