A comprehensive survey of intestine histopathological image analysis using machine vision approaches

Y Jing, C Li, T Du, T Jiang, H Sun, J Yang, L Shi… - Computers in Biology …, 2023 - Elsevier
Colorectal Cancer (CRC) is currently one of the most common and deadly cancers. CRC is
the third most common malignancy and the fourth leading cause of cancer death worldwide …

A review paper about deep learning for medical image analysis

B Sistaninejhad, H Rasi, P Nayeri - … and Mathematical Methods …, 2023 - Wiley Online Library
Medical imaging refers to the process of obtaining images of internal organs for therapeutic
purposes such as discovering or studying diseases. The primary objective of medical image …

GARL-Net: Graph based adaptive regularized learning deep network for breast cancer classification

V Patel, V Chaurasia, R Mahadeva, SP Patole - IEEE Access, 2023 - ieeexplore.ieee.org
Across the globe, women suffer from breast cancer fatal disease. It is arising surprisingly due
to a lack of awareness among them and the inconvenient reach of diagnostic systems. Many …

A convolution neural network with multi-level convolutional and attention learning for classification of cancer grades and tissue structures in colon histopathological …

M Dabass, S Vashisth, R Vig - Computers in biology and medicine, 2022 - Elsevier
A clinically comparable Convolutional Neural Network framework-based technique for
performing automated classification of cancer grades and tissue structures in hematoxylin …

A novel transfer learning approach for the classification of histological images of colorectal cancer

EF Ohata, JVS Chagas, GM Bezerra… - The Journal of …, 2021 - Springer
Colorectal cancer (CRC) is the second most diagnosed cancer in the United States. It is
identified by histopathological evaluations of microscopic images of the cancerous region …

Ensemble of adapted convolutional neural networks (CNN) methods for classifying colon histopathological images

D Albashish - PeerJ Computer Science, 2022 - peerj.com
Deep convolutional neural networks (CNN) manifest the potential for computer-aided
diagnosis systems (CADs) by learning features directly from images rather than using …

Use of dominant activations obtained by processing OCT images with the CNNs and slime mold method in retinal disease detection

M Toğaçar, B Ergen, V Tümen - Biocybernetics and Biomedical …, 2022 - Elsevier
Retinal disease is one of the diseases that cause visual symptoms or loss of vision in
humans. This disease can affect the choroid, which severely affects vision. Optical …

Detection and classification of Encephalon tumor using extreme learning machine learning algorithm based on Deep Learning Method

P Sahu, PK Sarangi, SK Mohapatra… - … Inspired Techniques in …, 2022 - Springer
The ordinary people cannot have the capability to detect and classify the brain tumor, 9 so
the radiologists or the clinical experts are the only person who can detect the encephalon …

A deep learning based approach to detect IDC in histopathology images

I Gupta, SR Nayak, S Gupta, S Singh, KD Verma… - Multimedia Tools and …, 2022 - Springer
Breast cancer is one of the widespread reasons of morbidity worldwide that begins in the
cells of the tissues of morbidity worldwide in the woman community. Breast cancer can be …

EL-CNN: An enhanced lightweight classification method for colorectal cancer histopathological images

XL Pan, B Hua, K Tong, X Li, JL Luo, H Yang… - … Signal Processing and …, 2025 - Elsevier
Colorectal cancer (CRC) histopathological image classification is a critical part of
diagnosing CRC. In this context, the classification efficiency of deep learning methods is …