AIMC Topic: Colonic Polyps

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Multiclassification of Endoscopic Colonoscopy Images Based on Deep Transfer Learning.

Computational and mathematical methods in medicine
With the continuous improvement of human living standards, dietary habits are constantly changing, which brings various bowel problems. Among them, the morbidity and mortality rates of colorectal cancer have maintained a significant upward trend. In ...

Artificial intelligence-based endoscopic diagnosis of colorectal polyps using residual networks.

PloS one
Convolutional neural networks (CNNs) are widely used for artificial intelligence (AI)-based image classification. Residual network (ResNet) is a new technology that facilitates the accuracy of image classification by CNN-based AI. In this study, we d...

Current status and limitations of artificial intelligence in colonoscopy.

United European gastroenterology journal
BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Further effor...

Prediction of the histology of colorectal neoplasm in white light colonoscopic images using deep learning algorithms.

Scientific reports
The treatment plan of colorectal neoplasm differs based on histology. Although new endoscopic imaging systems have been developed, there are clear diagnostic thresholds and requirements in using them. To overcome these limitations, we trained convolu...

Computational learning of features for automated colonic polyp classification.

Scientific reports
Shape, texture, and color are critical features for assessing the degree of dysplasia in colonic polyps. A comprehensive analysis of these features is presented in this paper. Shape features are extracted using generic Fourier descriptor. The nonsubs...

Colorectal polyp characterization with standard endoscopy: Will Artificial Intelligence succeed where human eyes failed?

Best practice & research. Clinical gastroenterology
The American Society for Gastrointestinal Endoscopy (ASGE) has proposed the "resect-and-discard" and "diagnose-and-leave" strategies for diminutive colorectal polyps to reduce the costs of unnecessary polyp resection and pathology evaluation. However...

A novel machine learning-based algorithm to identify and classify lesions and anatomical landmarks in colonoscopy images.

Surgical endoscopy
OBJECTIVES: Computer-aided diagnosis (CAD)-based artificial intelligence (AI) has been shown to be highly accurate for detecting and characterizing colon polyps. However, the application of AI to identify normal colon landmarks and differentiate mult...

Comparison of diagnostic performance between convolutional neural networks and human endoscopists for diagnosis of colorectal polyp: A systematic review and meta-analysis.

PloS one
Prospective randomized trials and observational studies have revealed that early detection, classification, and removal of neoplastic colorectal polyp (CP) significantly improve the prevention of colorectal cancer (CRC). The current effectiveness of ...

Colorectal polyp characterization with endocytoscopy: Ready for widespread implementation with artificial intelligence?

Best practice & research. Clinical gastroenterology
Endocytoscopy provides an in-vivo visualization of nuclei and micro-vessels at the cellular level in real-time, facilitating so-called "optical biopsy" or "virtual histology" of colorectal polyps/neoplasms. This functionality is enabled by 520-fold m...