AIMC Topic: Colonoscopy
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Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.
Scientific reports
Feb 18, 2025
Despite recent surge of interest in deploying colon capsule endoscopy (CCE) for early diagnosis of colorectal diseases, there remains a large gap between the current state of CCE in clinical practice, and the state of its counterpart optical colonosc...
Eye-tracking dataset of endoscopist-AI teaming during colonoscopy: Retrospective and real-time acquisition.
Scientific data
Feb 5, 2025
Recent studies have demonstrated that integrating AI into colonoscopy procedures significantly improves the adenoma detection rate (ADR) and reduces the adenoma miss rate (AMR). However, few studies address the critical issue of endoscopist-AI collab...
Impact of standard enhancement settings of endoscopy systems on performance of endoscopic artificial intelligence systems.
Endoscopy
Jan 30, 2025
BACKGROUND:  Artificial intelligence (AI) systems in endoscopy are predominantly developed and tested using high-quality imagery from expert centers. However, their performance may be different when applied in clinical practice, partly due to the div...
Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.
Scientific reports
Jan 25, 2025
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and a...
Synthesized colonoscopy dataset from high-fidelity virtual colon with abnormal simulation.
Computers in biology and medicine
Jan 17, 2025
With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-quality colonoscopy image datasets for training is crucial. However, the generalization ability of deep learning models is challenged by the limited ava...
Dynamic spectrum-driven hierarchical learning network for polyp segmentation.
Medical image analysis
Jan 14, 2025
Accurate automatic polyp segmentation in colonoscopy is crucial for the prompt prevention of colorectal cancer. However, the heterogeneous nature of polyps and differences in lighting and visibility conditions present significant challenges in achiev...
FocusUNet: Pioneering dual attention with gated U-Net for colonoscopic polyp segmentation.
Computers in biology and medicine
Jan 10, 2025
The detection and excision of colorectal polyps, precursors to colorectal cancer (CRC), can improve survival rates by up to 90%. Automated polyp segmentation in colonoscopy images expedites diagnosis and aids in the precise identification of adenomat...
Semi-Supervised Detection Model Based on Adaptive Ensemble Learning for Medical Images.
IEEE transactions on neural networks and learning systems
Jan 7, 2025
Introducing deep learning technologies into the medical image processing field requires accuracy guarantee, especially for high-resolution images relayed through endoscopes. Moreover, works relying on supervised learning are powerless in the case of ...
Evaluating the pathological and clinical implications of errors made by an artificial intelligence colon biopsy screening tool.
BMJ open gastroenterology
Jan 6, 2025
OBJECTIVE: Artificial intelligence (AI) tools for histological diagnosis offer great potential to healthcare, yet failure to understand their clinical context is delaying adoption. IGUANA (Interpretable Gland-Graphs using a Neural Aggregator) is an A...
[Telemedicine and AI-supported diagnostics in the daily routine of visceral medicine].
Chirurgie (Heidelberg, Germany)
Dec 30, 2024
Advances in telemedicine, exemplified by augmented reality (AR) and virtual reality (VR), are rapidly progressing. For instance, AR available over long distances has already been successfully utilized in crisis intervention, such as in war zones. The...
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