Ra-denet: Reverse attention and distractions elimination network for polyp segmentation
To address the problems of polyps of different shapes, sizes, and colors, low-contrast
polyps, various noise distractions, and blurred edges on colonoscopy, we propose the …
polyps, various noise distractions, and blurred edges on colonoscopy, we propose the …
An advanced diagnostic ColoRectalCADx utilises CNN and unsupervised visual explanations to discover malignancies
Colorectal cancer (CRC) is one of the most lethal kinds of cancer, so early detection is
critical. Three datasets, namely CNN transfer learning with discrete wavelet transform …
critical. Three datasets, namely CNN transfer learning with discrete wavelet transform …
A review on deep learning-based polyp segmentation for efficient colorectal cancer screening
The second largest cause of cancer-related deaths globally and the third most prevalent
cancer overall is colorectal cancer. Growths on the inner lining of these organs called polyps …
cancer overall is colorectal cancer. Growths on the inner lining of these organs called polyps …
Sub-band based attention for robust polyp segmentation
This article proposes a novel spectral domain based solution to the challenging polyp
segmentation. The main contribution is based on an interesting finding of the significant …
segmentation. The main contribution is based on an interesting finding of the significant …
DBE-Net: dual boundary-guided attention exploration network for polyp segmentation
H Ma, C Xu, C Nie, J Han, Y Li, C Liu - Diagnostics, 2023 - mdpi.com
Automatic segmentation of polyps during colonoscopy can help doctors accurately find the
polyp area and remove abnormal tissues in time to reduce the possibility of polyps …
polyp area and remove abnormal tissues in time to reduce the possibility of polyps …
CRPU-NET: a deep learning model based semantic segmentation for the detection of colorectal polyp in lower gastrointestinal tract
J Selvaraj, S Umapathy - Biomedical Physics & Engineering …, 2023 - iopscience.iop.org
Purpose. The objectives of the proposed work are twofold. Firstly, to develop a specialized
light weight CRPU-Net for the segmentation of polyps in colonoscopy images. Secondly, to …
light weight CRPU-Net for the segmentation of polyps in colonoscopy images. Secondly, to …
Parallel matters: Efficient polyp segmentation with parallel structured feature augmentation modules
The large variations of polyp sizes and shapes and the close resemblances of polyps to their
surroundings call for features with long‐range information in rich scales and strong …
surroundings call for features with long‐range information in rich scales and strong …
Automated Detection of Colorectal Polyp Utilizing Deep Learning Methods with Explainable AI
Detecting colorectal polyps promptly and accurately is crucial in preventing the progression
of colorectal cancer. These polyps cause severe conditions in the colon or rectum …
of colorectal cancer. These polyps cause severe conditions in the colon or rectum …
Reduced volume of diabetic pancreatic islets in rodents detected by synchrotron X-ray phase-contrast microtomography and deep learning network
The pancreatic islet is a highly structured micro-organ that produces insulin in response to
rising blood glucose. Here we develop a label-free and automatic imaging approach to …
rising blood glucose. Here we develop a label-free and automatic imaging approach to …
Advancing colorectal polyp detection: an automated segmentation approach with colrectseg-unet
J Selvaraj, S Umapathy, NA Rajesh - … : Applications, Basis and …, 2024 - World Scientific
Purpose: This study aimed to achieve two primary goals. First, we sought to develop a
lightweight convolutional neural network (CNN) model, COLRECTSEG-UNet, for the …
lightweight convolutional neural network (CNN) model, COLRECTSEG-UNet, for the …