AI Medical Compendium Topic

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Colonic Polyps

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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...

Artificial intelligence: Thinking outside the box.

Best practice & research. Clinical gastroenterology
Artificial intelligence (AI) for luminal gastrointestinal endoscopy is rapidly evolving. To date, most applications have focused on colon polyp detection and characterization. However, the potential of AI to revolutionize our current practice in endo...

Impact of artificial intelligence on colorectal polyp detection.

Best practice & research. Clinical gastroenterology
Since colonoscopy and polypectomy were introduced, Colorectal Cancer (CRC) incidence and mortality decreased significantly. Although we have entered the era of quality measurement and improvement, literature shows that a considerable amount of colore...

A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography.

International journal of computer assisted radiology and surgery
PURPOSE: Deep learning can be used for improving the performance of computer-aided detection (CADe) in various medical imaging tasks. However, in computed tomographic (CT) colonography, the performance is limited by the relatively small size and the ...