It is very important to diagnose patients with rectal cancer, which can provide reference for
the follow-up treatment. The gold standard for rectal cancer diagnosis is biopsy, but biopsy is …

Medical image analysis is crucial in healthcare research. The convolutional neural network
(CNN) has great potential in improving the precision and speed of medical diagnosis. In …

Colorectal Cancer (CRC) is a prevalent and deadly disease, and accurate and timely
diagnosis is essential for improving patient outcomes. The use of deep learning in medical …

This paper investigates a deep learning method in image classification for the detection of
colorectal cancer with ResNet architecture. The exceptional performance of a deep learning …

Colorectal cancer refers to cancer of the colon or rectum; and has high incidence rates
worldwide. Colorectal cancer most often occurs in the form of adenocarcinoma, which is …

Background and objective: Colorectal cancer (CRC) is currently one of the main cancers
world-wide, with a high incidence in the elderly. In the diagnosis of CRC, endorectal …

The importance of histopathological image analysis in the early detection of colorectal
cancer cannot be overstated. Because of the subjective nature of the evaluation, visual …

We developed a deep learning classifier of rectal cancer response (tumor vs. no-tumor) to
total neoadjuvant treatment (TNT) from endoscopic images acquired before, during, and …

The purpose of this study is to evaluate transfer learning with deep convolutional neural
networks for the classification of abdominal ultrasound images. Grayscale images from 185 …

Histopathological image analysis is vital for timely colorectal cancer diagnosis. Our study
uses transfer learning techniques to create an efficient and robust classification method …