ArticleHernia : the journal of hernias and abdominal wall surgery2024
Anatomical recognition of dissection layers, nerves, vas deferens, and microvessels using artificial intelligence during transabdominal preperitoneal inguinal hernia repair.
Article in Hernia : the journal of hernias and abdominal wall surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Artificial intelligence-based anatomical segmentation in transabdominal preperitoneal repair of groin hernia.Hernia : the journal of hernias and abdominal wall surgery · 2026Article
- Histopathological proof-of-concept validation of AI-assisted peripheral neural track recognition during laparoscopic gastrointestinal surgery.Surgical endoscopy · 2026Article
- Intraoperative real-time recognition of dissectible layers by artificial intelligence is useful in laparoscopic inguinal hernia repair.Surgical endoscopy · 2026Article
- Reply to: Surgical scene understanding and the emerging challenge of independent validation in an industry-led AI ecosystem.NPJ digital medicine · 2026Article
- External validation and clinical readiness of intraoperative video AI in general surgery: a systematic review.Surgery today · 2026Review
- Mapping the global landscape of robot-assisted hernia surgery research: a bibliometric analysis.Journal of robotic surgery · 2026Article
- Review
- Application of machine learning and deep learning in the diagnosis and treatment of inguinal hernia: a narrative review.Frontiers in medicine · 2026Review
- Artificial Intelligence in Gastrointestinal Surgery: A Systematic Review of Its Role in Laparoscopic and Robotic Surgery.Journal of personalized medicine · 2025Review
- Landmark display system for laparoscopic inguinal hernia repair using artificial intelligence.Surgical endoscopy · 2025Article
- Modern Perspectives on Inguinal Hernia Repair: A Narrative Review on Surgical Techniques, Mesh Selection and Fixation Strategies.Journal of clinical medicine · 2025Review
- Advances in Surgery and Sustainability: The Use of AI Systems and Reusable Devices in Laparoscopic Colorectal Surgery.Cancers · 2025Review
- Increased length of incarcerated small bowel as a risk factor for intestinal necrosis in obturator hernia.Hernia : the journal of hernias and abdominal wall surgery · 2024Article
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Authors and funding
10 authors.
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Abstract
purposeIn laparoscopic inguinal hernia surgery, proper recognition of loose connective tissue, nerves, vas deferens, and microvessels is important to prevent postoperative complications, such as recurrence, pain, sexual dysfunction, and bleeding. EUREKA (Anaut Inc., Tokyo, Japan) is a system that uses artificial intelligence (AI) for anatomical recognition. This system can intraoperatively confirm the aforementioned anatomical landmarks. In this study, we validated the accuracy of EUREKA in recognizing dissection layers, nerves, vas deferens, and microvessels during transabdominal preperitoneal inguinal hernia repair (TAPP).
methodsWe used TAPP videos to compare EUREKA's recognition of loose connective tissue, nerves, vas deferens, and microvessels with the original surgical video and examined whether EUREKA accurately identified these structures. Intersection over Union (IoU) and F1/Dice scores were calculated to quantitively evaluate AI predictive images.
resultsThe mean IoU and F1/Dice scores were 0.33 and 0.50 for connective tissue, 0.24 and 0.38 for nerves, 0.50 and 0.66 for the vas deferens, and 0.30 and 0.45 for microvessels, respectively. Compared with the images without EUREKA visualization, dissection layers were very clearly recognized and displayed when appropriate tension was applied.
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