SegExtension:A Lightweight Segmentation Extension Based on 3D Slicer

The role of medical image detection and segmentation in medical treatment is increasingly prominent. It provides users with timely and accurate diagnostic and therapeutic information, thereby improving the efficiency of medical care. However, the current clinical practice often relies on medical image segmentation methods that require significant human-machine interaction, falling under the category of semi-automatic segmentation. These methods are limited by their dependence on users and face challenges regarding efficiency, accuracy, and precision.To address these issues, we propose an automated medical image segmentation method using advanced deep learning models. We have developed a plugin that integrates this method into open-source medical image processing software, facilitating its use by industry professionals. The results obtained from testing on medical images of different organs demonstrate the high accuracy of our automated segmentation tool, highlighting its efficiency and precision advantages.