CREATION OF A PERSONALIZED ULTRASOUND IMAGE DATABASE AND 3D MODEL RECONSTRUCTION USING ARTIFICIAL INTELLIGENCE
Keywords:
Ultrasound imaging; medical image database; artificial intelligence; deep learning; 3D reconstruction; medical robotics.Abstract
Ultrasound imaging is one of the most widely used diagnostic techniques due to its safety, low cost, and real-time imaging capabilities. However, conventional ultrasound diagnostics strongly depend on operator experience and provide limited spatial perception due to their two-dimensional nature. This paper presents a comprehensive approach for creating a personalized ultrasound image database and reconstructing three-dimensional (3D) anatomical models using artificial intelligence (AI). The proposed system integrates structured data acquisition, image annotation, deep learning–based segmentation, and 3D reconstruction techniques to generate patient-specific anatomical models. The resulting 3D representations enhance diagnostic accuracy, improve visualization, and enable seamless integration with intelligent medical robotic systems. Experimental results demonstrate that the proposed approach significantly improves segmentation accuracy and 3D reconstruction quality, making it suitable for clinical decision support and robotic-assisted ultrasound applications.
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