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Liver cancer is one of the most common cancers in the world, and the most important current clinical treatment for liver cancer is surgery. Posture matching with augmented reality navigation for laparoscopic hepatic resection facilitates the surgeon to achieve precise liver resection, and the liver ridgeline and falciform ligament of intraoperative laparoscopic images are very important features. Since the traditional methods of extracting liver ridgeline and ligament are extracted from liver CT images or surface grids, there are drawbacks such as many manual interactions. In order to solve the above problems, this paper proposes PointNet-based feature extraction of falciform ligaments and ridgeline in preoperative 3D point clouds of the liver, which is able to extract falciform ligaments and ridgeline directly on the 3D model of the liver, and the extraction results are concise, clear and efficient.
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