Research on Multimodal Medical Image Feature Fusion Algorithm and Development of Intelligent Diagnosis Model

This research direction focuses on the development of multimodal medical image feature fusion algorithms and intelligent diagnosis models. Aiming at the clinical limitations of insufficient feature representation, limited lesion recognition ability and low quantitative diagnosis accuracy of single-modal medical images, this work conducts systematic research on standardized image preprocessing, multimodal registration and alignment, and deep feature fusion based on CT, MRI, ultrasound and other mainstream medical imaging data. This research constructs high-precision and interpretable models for lesion segmentation, disease classification and intelligent evaluation, effectively explores complementary information from multimodal images, improves the capabilities of intelligent disease diagnosis and quantitative analysis, and provides core algorithmic and technical support for clinical precise imaging diagnosis.