Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis-Reference-Cited by-同舟云学术

Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis

Published:2023-08-02 Issue:6 Volume:36 Page:2602-2612
ISSN:0897-1889
Container-title:Journal of Digital Imaging
language:en
Short-container-title:J Digit Imaging

Author:

Morovati Bahareh,Lashgari Reza,Hajihasani Mojtaba,Shabani Hasti^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

https://link.springer.com/content/pdf/10.1007/s10278-023-00887-w.pdf

Reference31 articles.

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3. Boyle P, Levin B: World cancer report 2008, IARC Press, International Agency for Research on Cancer, 2008

4. Arevalo J, Cruz-Roa A, Gonzalez O FA: Histopathology image representation for automatic analysis a state-of-the-art review. Revista Med 22(2):79-91, 2014

5. Singh S, Kumar R: Breast cancer detection from histopathology images with deep inception and residual blocks. Multimed Tools Appl 81(4):5849-5865, 2022

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