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Colonoscopy

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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 ...

Hartmann's procedure vs abdominoperineal resection with intersphincteric dissection in patients with rectal cancer: a randomized multicentre trial (HAPIrect).

BMC surgery
BACKGROUND: The use of Hartmann's procedure in the old and frail and/or in patients with fecal incontinence is increasing, even though some data have reported high postoperative rates of pelvic abscesses. Abdominoperineal excision with intersphincter...

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

IEEE transactions on medical imaging
Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper convergence. A promising alternative is to fine-tune a CNN that ha...

Quantitative assessment of colorectal morphology: Implications for robotic colonoscopy.

Medical engineering & physics
This paper presents a method of characterizing the distribution of colorectal morphometrics. It uses three-dimensional region growing and topological thinning algorithms to determine and visualize the luminal volume and centreline of the colon, respe...