preprint-Pham.pdf (3.29 MB)
Download file

Extracting Time-Frequency Features of Images for Robust LSTM-based Classification of H&E Stained Tissue

Download (3.29 MB)
posted on 2020-12-08, 14:20 authored by Tuan PhamTuan Pham
The importance of automated classification of histopathological images has been increasingly recognized for effective processing of large volumes of data in the era of digital pathology for new discovery of disease mechanism. This paper presents a deep-learning approach that extracts time-frequency features of H&E stained tissue images for classification by long short-term memory networks. Using two large public databases of colorectal-cancer and heart-failure H&E stained tissue images, the proposed approach outperforms several state-of-the-art benchmark classification methods, including support vector machines and convolutional neural networks in terms of several statistical measures.


Email Address of Submitting Author

ORCID of Submitting Author


Submitting Author's Institution

Prince Mohammad Bin Fahd University

Submitting Author's Country

  • Saudi Arabia

Usage metrics