ArticleScientific reports2022
Assessment of blood perfusion quality in laparoscopic colorectal surgery by means of Machine Learning.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Efficacy and safety of indocyanine green fluorescence imaging in colorectal cancer: a systematic review and meta-analysis of randomized controlled trials.International journal of colorectal disease · 2025Pooled it
- Quantification of indocyanine green fluorescence angiography in colorectal surgery: a systematic review of the literature.Surgical endoscopy · 2025Pooled it
- Beyond robotic platforms: artificial intelligence and the emergence of intelligent surgical ecosystems in colorectal surgery.Journal of robotic surgery · 2026Review
- Fluorescence-guided surgery in colorectal cancer: current evidence, quantitative advances, and future perspectives.Annals of coloproctology · 2026Review
- Guiding esophagectomy with intraoperative NIR-II fluorescence video imaging and rapid computation.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Pushing the boundaries of indocyanine green fluorescence angiography in colorectal surgery.Updates in surgery · 2025Article
- Artificial Intelligence in Gastrointestinal Surgery: A Systematic Review of Its Role in Laparoscopic and Robotic Surgery.Journal of personalized medicine · 2025Review
- A Novel Deep Learning Model for Predicting Colorectal Anastomotic Leakage: A Pioneer Multicenter Transatlantic Study.Journal of clinical medicine · 2025Article
- Use of artificial intelligence in the analysis of digital videos of invasive surgical procedures: scoping review.BJS open · 2025Article
- Biophysical modeling and artificial intelligence for quantitative assessment of anastomotic blood supply in laparoscopic low anterior rectal resection.Surgical endoscopy · 2025Article
- AUGUR-AIM: Clinical validation of an artificial intelligence indocyanine green fluorescence angiography expert representer.Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland · 2025Observational
- Left colic artery-preserving radical rectal cancer surgery: a literature review.Frontiers in surgery · 2025Review
- Near-infrared indocyanine green angiography in recognizing bowel ischemia in emergency surgery: game changer or overrated?Innovative surgical sciences · 2024Review
- Quadruple Assessment of Colorectal Anastomosis after Laparoscopic Rectal Resection: A Retrospective Analysis of a Propensity-Matched Cohort.Journal of clinical medicine · 2024Article
- Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery.Heliyon · 2024Article
- Fluorescence-guided minimally-invasive resection of abdominal paragangliomas using indocyanine green.Scientific reports · 2024Article
- Uncovering the Correlation between COVID-19 and Neurodegenerative Processes: Toward a New Approach Based on EEG Entropic Analysis.Bioengineering (Basel, Switzerland) · 2023Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An innovative algorithm to automatically assess blood perfusion quality of the intestinal sector in laparoscopic colorectal surgery is proposed. Traditionally, the uniformity of the brightness in indocyanine green-based fluorescence consists only in a qualitative, empirical evaluation, which heavily relies on the surgeon's subjective assessment. As such, this leads to assessments that are strongly experience-dependent. To overcome this limitation, the proposed algorithm assesses the level and uniformity of indocyanine green used during laparoscopic surgery. The algorithm adopts a Feed Forward Neural Network receiving as input a feature vector based on the histogram of the green band of the input image. It is used to (i) acquire information related to perfusion during laparoscopic colorectal surgery, and (ii) support the surgeon in assessing objectively the outcome of the procedure. In particular, the algorithm provides an output that classifies the perfusion as adequate or inadequate. The algorithm was validated on videos captured during surgical procedures carried out at the University Hospital Federico II in Naples, Italy. The obtained results show a classification accuracy equal to [Formula: see text], with a repeatability of [Formula: see text]. Finally, the real-time operation of the proposed algorithm was tested by analyzing the video streaming captured directly from an endoscope available in the OR.
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