Design and Integration of Artificial Intelligence in Laparoscopy for Enhanced Visualisation

The design and integration of Artificial Intelligence (AI) in laparoscopy represents a major advancement for minimally invasive surgery. The main objective of the proposed project in this paper is to transform laparoscopic practice by exploiting the potential of AI to improve surgical precision and minimize human errors. By relying on real-time image analysis algorithms, the proposed system will be able to detect, segment and classify anatomical structures with increased accuracy and enhanced visualization. In addition, it will integrate interactive learning tools to enhance surgeon training, including simulation and assessment in a virtual environment. By optimizing surgical protocols and standardizing practices, this innovation aims to strengthen patient safety, reduce postoperative complications, and promote more efficient surgery. The proposed solution combines a cutting-edge technological approach with in-depth clinical thinking, paving the way for widespread adoption of AI in operating rooms.

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Publication Details

Published
2025-08-08
DOI
https://doi.org/10.1109/icbmesh66209.2025.11182204
Primary Topic
Surgical Simulation and Training
Type
article
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Design and Integration of Artificial Intelligence in Laparoscopy for Enhanced Visualisation

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Surgical Simulation and Training
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Design and Integration of Artificial Intelligence in Laparoscopy for Enhanced Visualisation

Rishi Manoj, G Darsana, M. Doucouré, Sai Kiran Goud Routhu, A. Fall, Siva Shankara Raju Vysyaraju
article en

Abstract

The design and integration of Artificial Intelligence (AI) in laparoscopy represents a major advancement for minimally invasive surgery. The main objective of the proposed project in this paper is to transform laparoscopic practice by exploiting the potential of AI to improve surgical precision and minimize human errors. By relying on real-time image analysis algorithms, the proposed system will be able to detect, segment and classify anatomical structures with increased accuracy and enhanced visualization. In addition, it will integrate interactive learning tools to enhance surgeon training, including simulation and assessment in a virtual environment. By optimizing surgical protocols and standardizing practices, this innovation aims to strengthen patient safety, reduce postoperative complications, and promote more efficient surgery. The proposed solution combines a cutting-edge technological approach with in-depth clinical thinking, paving the way for widespread adoption of AI in operating rooms.

Chennai Mathematical Institute (IN), Mali-Folkecenter (ML), Naval Science & Technological Laboratory (IN), Biomedical Enterprises (United States) (US), World Economic Forum (CH)
Openalex Percentile: Top 57%
Surgical Simulation and Training
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