AIMC Topic: Colonoscopy

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Computer-Aided Diagnosis Based on Convolutional Neural Network System for Colorectal Polyp Classification: Preliminary Experience.

Oncology
BACKGROUND AND AIM: Computer-aided diagnosis (CAD) is becoming a next-generation tool for the diagnosis of human disease. CAD for colon polyps has been suggested as a particularly useful tool for trainee colonoscopists, as the use of a CAD system avo...

Full-driving soft robotic colonoscope in compliant colon tissue.

Journal of medical engineering & technology
Robotic colonoscopy is an efficient examination method for finding malignant tumour in its early stage. This research developed a novel robotic endoscope with 13 mm diameter, 105 mm length and 22.3 g weight. A contact biomechanical model is proposed ...

Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model.

Gut
BACKGROUND: In general, academic but not community endoscopists have demonstrated adequate endoscopic differentiation accuracy to make the 'resect and discard' paradigm for diminutive colorectal polyps workable. Computer analysis of video could poten...

Performance analysis of a machine learning flagging system used to identify a group of individuals at a high risk for colorectal cancer.

PloS one
Individuals with colorectal cancer (CRC) have a tendency to intestinal bleeding which may result in mild to severe iron deficiency anemia, but for many colon cancer patients hematological abnormalities are subtle. The fecal occult blood test (FOBT) i...

Design and preliminary evaluation of a self-steering, pneumatically driven colonoscopy robot.

Journal of medical engineering & technology
Colonoscopy is a diagnostic procedure to detect pre-cancerous polyps and tumours in the colon, and is performed by inserting a long tube equipped with a camera and biopsy tools. Despite the medical benefits, patients undergoing this procedure often c...

Correlating Quantitative Fecal Immunochemical Test Results with Neoplastic Findings on Colonoscopy in a Population-Based Colorectal Cancer Screening Program: A Prospective Study.

Canadian journal of gastroenterology & hepatology
. The Canadian Partnership Against Cancer (CPAC) recommends a fecal immunochemical test- (FIT-) positive predictive value (PPV) for all adenomas of ≥50%. We sought to assess FIT performance among average-risk participants of the British Columbia Colo...

Integrating Online and Offline Three-Dimensional Deep Learning for Automated Polyp Detection in Colonoscopy Videos.

IEEE journal of biomedical and health informatics
Automated polyp detection in colonoscopy videos has been demonstrated to be a promising way for colorectal cancer prevention and diagnosis. Traditional manual screening is time consuming, operator dependent, and error prone; hence, automated detectio...

Automatic Detection and Classification of Colorectal Polyps by Transferring Low-Level CNN Features From Nonmedical Domain.

IEEE journal of biomedical and health informatics
Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide. Although polypectomy at early stage reduces CRC incidence, 90% of the polyps are small and diminutive, where removal of them poses risks to patients that may outweigh the benefits...

Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification.

Computational and mathematical methods in medicine
Recently, Deep Learning, especially through Convolutional Neural Networks (CNNs) has been widely used to enable the extraction of highly representative features. This is done among the network layers by filtering, selecting, and using these features ...