AIMC Topic: Colonic Polyps

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

Surgical endoscopy Feb 16, 2021
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...
Humans Algorithms Colonoscopy Colonic Polyps Artificial Intelligence Machine Learning
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Comparison of diagnostic performance between convolutional neural networks and human endoscopists for diagnosis of colorectal polyp: A systematic review and meta-analysis.

PloS one Feb 16, 2021
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 ...
Humans Endoscopy, Digestive System Neural Networks, Computer Colonic Polyps
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Colorectal polyp characterization with endocytoscopy: Ready for widespread implementation with artificial intelligence?

Best practice & research. Clinical gastroenterology Dec 18, 2020
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...
Colonoscopy Endoscopy Humans Colorectal Neoplasms Colonic Polyps Artificial Intelligence
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Artificial intelligence: Thinking outside the box.

Best practice & research. Clinical gastroenterology Dec 5, 2020
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...
Colonic Polyps Learning Endoscopy, Gastrointestinal Humans Artificial Intelligence
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Impact of artificial intelligence on colorectal polyp detection.

Best practice & research. Clinical gastroenterology Dec 4, 2020
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...
Colonic Polyps Humans Colorectal Neoplasms Colonoscopy Artificial Intelligence Incidence Retrospective Studies
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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 Nov 5, 2020
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 ...
Colonoscopy Deep Learning Colonography, Computed Tomographic Colonic Polyps Humans Neural Networks, Computer Sensitivity and Specificity
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Real-time unblinding for validation of a new CADe tool for colorectal polyp detection.

Gut Oct 12, 2020
Humans Neural Networks, Computer Colonoscopy Diagnosis, Computer-Assisted Pilot Projects Software Prospective Studies Colonic Polyps
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Improving CNN training on endoscopic image data by extracting additionally training data from endoscopic videos.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Oct 7, 2020
In this work we present a technique to deal with one of the biggest problems for the application of convolutional neural networks (CNNs) in the area of computer assisted endoscopic image diagnosis, the insufficient amount of training data. Based on p...
Image Processing, Computer-Assisted Colonic Polyps Humans Neural Networks, Computer Diagnosis, Computer-Assisted
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Application of Deep Learning for Early Screening of Colorectal Precancerous Lesions under White Light Endoscopy.

Computational and mathematical methods in medicine Aug 18, 2020
METHODS: We collected and sorted out the white light endoscopic images of some patients undergoing colonoscopy. The convolutional neural network model is used to detect whether the image contains lesions: CRC, colorectal adenoma (CRA), and colorectal...
Image Interpretation, Computer-Assisted Neural Networks, Computer Light Deep Learning Diagnostic Errors Colorectal Neoplasms Colonic Polyps Precancerous Conditions Computational Biology Mass Screening Humans Colonoscopy Intestinal Polyps Adenoma
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Deep learning to find colorectal polyps in colonoscopy: A systematic literature review.

Artificial intelligence in medicine Aug 1, 2020
Colorectal cancer has a great incidence rate worldwide, but its early detection significantly increases the survival rate. Colonoscopy is the gold standard procedure for diagnosis and removal of colorectal lesions with potential to evolve into cancer...
Colonic Polyps Deep Learning Early Detection of Cancer Colorectal Neoplasms Colonoscopy Humans Reproducibility of Results
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