Artificial Intelligence (AI) technologies play a significant role and significantly impact various
sectors, including healthcare, engineering, sciences, and smart cities. AI has the potential to …

Objective To validate the newly developed artificial intelligence (AI)-assisted simulation by
evaluating the speed of three-dimensional (3D) reconstruction and accuracy of segmental …

In clinical practice, automatic polyp segmentation from colonoscopy images is an effective
assistant manner in the early detection and prevention of colorectal cancer. This paper …

Limb salvage surgery of malignant pelvic tumors is the most challenging procedure in
musculoskeletal oncology due to the complex anatomy of the pelvic bones and soft tissues …

During the past decades, many automated image analysis methods have been developed
for colonoscopy. Real-time implementation of the most promising methods during …

Background and Aims Recently, the use of computer-aided detection (CADe) for
colonoscopy has been investigated to improve the adenoma detection rate (ADR). We …

Background and Aims Publicly available databases containing colonoscopic imaging data
are valuable resources for artificial intelligence (AI) research. Currently, little is known …

Computer-aided polyp segmentation is a crucial task that supports gastroenterologists in
examining and resecting anomalous tissue in the gastrointestinal tract. The disease polyps …

The Human Genome Project, completed in 2003 by an international consortium, is
considered one of the most important achievements for mankind in the 21st century [1]. With …

Several studies have shown a significant adenoma miss rate up to 35% during screening
colonoscopy, especially in patients with diminutive adenomas. The use of artificial …