Surgical area recognition from laparoscopic images in laparoscopic gastrectomy for gastric cancer using label smoothing and uncertainty

Yuichiro Hayashi; Kazunari Misawa; Kensaku Mori

doi:10.1117/12.2654775

3 April 2023 Surgical area recognition from laparoscopic images in laparoscopic gastrectomy for gastric cancer using label smoothing and uncertainty

Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

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Proceedings Volume 12466, Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling; 1246624 (2023) https://doi.org/10.1117/12.2654775
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

This paper presents surgical area recognition from laparoscopic images in laparoscopic gastrectomy. Laparoscopic gastrectomy is performed as a minimally invasive procedure for removing gastric cancer. In this surgery, surgeons should cut the blood vessels around the stomach before resecting cancer. Since this type of surgery requires higher surgical skill, a surgical assistance system has been developed to enhance surgeons’ abilities. Recognition of the surgical area related to the blood vessels from laparoscopic videos provides essential information in the operative field to the surgical assistance system. Therefore, we develop a method for recognizing laparoscopic images into the surgical area. The proposed method classifies the laparoscopic images into seven scenes using deep neural networks. We introduce the label smoothing in time direction to obtain a soft label. Bayesian neural networks are used to classify the laparoscopic images and estimate the uncertainty. After the classification, we modify the predictions on each laparoscopic image using the estimated uncertainty and temporal information. We evaluated the proposed method using 10,818 images from ten videos recorded during laparoscopic gastrectomy for gastric cancer. Five-fold cross-validation was performed for the performance evaluation. The mean classification accuracy was 84.0%. The experimental results showed that the proposed method could recognize the surgical area from laparoscopic images.

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Yuichiro Hayashi, Kazunari Misawa, and Kensaku Mori "Surgical area recognition from laparoscopic images in laparoscopic gastrectomy for gastric cancer using label smoothing and uncertainty", Proc. SPIE 12466, Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling, 1246624 (3 April 2023); https://doi.org/10.1117/12.2654775

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KEYWORDS

Laparoscopy

Surgery

Image classification

Video

Cancer

Blood vessels

Neural networks

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