AIMC Topic: Colonoscopy

Clear Filters Showing 271 to 280 of 353 articles

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...

Colonoscopy with robotic steering and automated lumen centralization: a feasibility study in a colon model.

Endoscopy
BACKGROUND AND STUDY AIMS: We introduced a new platform for performing colonoscopy with robotic steering and automated lumen centralization (RS-ALC) and evaluated its technical feasibility.

Current state of micro-robots/devices as substitutes for screening colonoscopy: assessment based on technology readiness levels.

Surgical endoscopy
BACKGROUND: Previous reports have described several candidates, which have the potential to replace colonoscopy, but to date, there is still no device capable of fully replacing flexible colonoscopy in the management of colonic disorders and for mass...

Polyp Detection via Imbalanced Learning and Discriminative Feature Learning.

IEEE transactions on medical imaging
Recent achievement of the learning-based classification leads to the noticeable performance improvement in automatic polyp detection. Here, building large good datasets is very crucial for learning a reliable detector. However, it is practically chal...

Natural language processing as an alternative to manual reporting of colonoscopy quality metrics.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The adenoma detection rate (ADR) is a quality metric tied to interval colon cancer occurrence. However, manual extraction of data to calculate and track the ADR in clinical practice is labor-intensive. To overcome this difficulty...

Multi-center colonoscopy quality measurement utilizing natural language processing.

The American journal of gastroenterology
BACKGROUND: An accurate system for tracking of colonoscopy quality and surveillance intervals could improve the effectiveness and cost-effectiveness of colorectal cancer (CRC) screening and surveillance. The purpose of this study was to create and te...

Applying machine learning to predict bowel preparation adequacy in elderly patients for colonoscopy: development and validation of a web-based prediction tool.

Annals of medicine
BACKGROUND: Adequate bowel preparation is crucial for effective colonoscopy, especially in elderly patients who face a high risk of inadequate preparation. This study develops and validates a machine learning model to predict bowel preparation adequa...

Guideline-driven clinical decision support for colonoscopy patients using the hierarchical multi-label deep learning method.

Chinese medical journal
BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical...