AIMC Topic: Colonic Polyps

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PGMNet: a polyp segmentation network based on bit-plane slicing and multi-scale adaptive fusion.

Biomedical physics & engineering express
Accurate detection and segmentation of polyps during colonoscopy are of great significance for the early prevention and treatment of colorectal cancer. However, due to the considerable variations in polyp size and shape, as well as their blurred boun...

Multi-scale aggregation network for colonoscopic polyp segmentation via frequency domain decoupling.

Scientific reports
Automated segmentation of colorectal polyps is of great significance for early screening and clinical intervention of colorectal cancer. However, the diversity of polyp morphology and the uneven contrast caused by illumination changes in colonoscopy ...

Improving Colorectal Cancer Detection with AI-Assisted Colonoscopy: A Systematic Review and Meta-Analysis of 38 RCTs with GRADE Assessment.

Journal of gastrointestinal cancer
BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Early detection of precancerous lesions such as adenomas and polyps is vital for prevention, yet standard colonoscopy may miss up to 26% of adenomas. A...

Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled Trial.

Gut and liver
BACKGROUND/AIMS: Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems have been introduced to increase the polyp detection rate (PDR) during colonoscopy, potentially enhanc...

Structured Integration of an Artificial Intelligence-Based System for the Optical Diagnosis of Colorectal Polyps.

Gut and liver
BACKGROUND/AIMS: Recent advances in computer-aided diagnosis (CADx) systems have demonstrated expert-level accuracy in the optical diagnosis of colorectal polyps. High-confidence (HC) diagnoses have been defined as those made within 3 seconds without...

Deep learning with refined single candidate optimizer for early polyp detection.

Scientific reports
Colorectal cancer (CRC) is one of the most common sources of cancer-related death worldwide. Early detection of these precancerous polyps with the aid of colonoscopy plays an important role in decreasing the burden of CRC. By employing novel optimiza...

Colonoscopy Quality and Strategies for Improvement.

Gut and liver
Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and mortality. Its effectiveness depends on colonoscopist performance, which can vary. Missed lesions during colonoscopy can lead to post-colonoscopy CRC ...

HSSAM-Net: hyper-scale shifted aggregation network for precise colorectal polyp segmentation in endoscopic images.

Scientific reports
Colorectal cancer remains a leading cause of cancer-related mortality worldwide, emphasizing the importance of early detection through accurate polyp identification. However, colonoscopy relies heavily on precise polyp segmentation in endoscopic imag...

Effectiveness of artificial intelligence-assisted colonoscopy in detecting and diagnosing colorectal tumors: a systematic review and network meta-analysis.

International journal of colorectal disease
BACKGROUND: The emergence of artificial intelligence (AI) has greatly promoted the development of the field of medical image analysis, but the potential benefits of AI-assisted colonoscopy and diagnosis (CADe/CADx) for the detection rate of colorecta...