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Colorectal polyp region extraction using saliency detection network with neutrosophic enhancement
Colorectal polyp recognition is crucial for early colorectal cancer detection and treatment.
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
[HTML][HTML] Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions
M Viscaino, JT Bustos, P Muñoz… - World Journal of …, 2021 - ncbi.nlm.nih.gov
Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due
to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular …
to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular …
Attention based multi-scale parallel network for polyp segmentation
P Song, J Li, H Fan - Computers in Biology and Medicine, 2022 - Elsevier
Colonoscopy is an effective method for detecting colorectal polyps and preventing colorectal
cancer. Therefore, in clinical practice, it is very important to accurately segment the location …
cancer. Therefore, in clinical practice, it is very important to accurately segment the location …
[HTML][HTML] Comprehensive review of publicly available colonoscopic imaging databases for artificial intelligence research: availability, accessibility, and usability
BBSL Houwen, KJ Nass, JLA Vleugels… - Gastrointestinal …, 2023 - Elsevier
Background and Aims Publicly available databases containing colonoscopic imaging data
are valuable resources for artificial intelligence (AI) research. Currently, little is known …
are valuable resources for artificial intelligence (AI) research. Currently, little is known …
Boundary-aware context neural network for medical image segmentation
Medical image segmentation can provide a reliable basis for further clinical analysis and
disease diagnosis. With the development of convolutional neural networks (CNNs), medical …
disease diagnosis. With the development of convolutional neural networks (CNNs), medical …
PolypSegNet: A modified encoder-decoder architecture for automated polyp segmentation from colonoscopy images
Colorectal cancer has become one of the major causes of death throughout the world. Early
detection of Polyp, an early symptom of colorectal cancer, can increase the survival rate to …
detection of Polyp, an early symptom of colorectal cancer, can increase the survival rate to …
PPNet: Pyramid pooling based network for polyp segmentation
Colonoscopy is the gold standard method for investigating the gastrointestinal tract.
Localizing the polyps in colonoscopy images plays a vital role when doing a colonoscopy …
Localizing the polyps in colonoscopy images plays a vital role when doing a colonoscopy …
An ensemble-based deep convolutional neural network for computer-aided polyps identification from colonoscopy
Colorectal cancer (CRC) is the third leading cause of cancer death globally. Early detection
and removal of precancerous polyps can significantly reduce the chance of CRC patient …
and removal of precancerous polyps can significantly reduce the chance of CRC patient …
SR-AttNet: An interpretable stretch–relax attention based deep neural network for polyp segmentation in colonoscopy images
Background: Colorectal polyp is a common structural gastrointestinal (GI) anomaly, which
can in certain cases turn malignant. Colonoscopic image inspection is, thereby, an important …
can in certain cases turn malignant. Colonoscopic image inspection is, thereby, an important …
Contour-aware polyp segmentation in colonoscopy images using detailed upsampling encoder-decoder networks
Colorectal cancer has become one of the most common cause of cancer mortality
worldwide, with a five-year survival rate of over 50%. Additionally, the potential of some …
worldwide, with a five-year survival rate of over 50%. Additionally, the potential of some …