Exploration of Multi-Scale Image Fusion Systems in Intelligent Medical Image Analysis

• DOI: 10.48550/arxiv.2406.18548
• Publication Date: 2024-05-23
• Authors: Yu-xiang Hu; Haowei Yang; Ting Xu; Shuyao He; Jiajie Yuan; Haozhang Deng
• Keywords: FOS: Computer and information sciences; Computer Vision and Pattern Recognition (cs.CV); Image and Video Processing (eess.IV); Computer Science - Computer Vision and Pattern Recognition; FOS: Electrical engineering, electronic engineering, information engineering; Electrical Engineering and Systems Science - Image and Video Processing

The diagnosis of brain cancer relies heavily on medical imaging techniques, with MRI being the most commonly used. It is necessary to perform automatic segmentation tumors images. This project intends build an algorithm based U-Net. residual network and module used enhance context information are combined, void space convolution pooling pyramid added for processing. glioma image dataset provided by archives was experimentally verified. A multi-scale method a weighted least squares filter complete 3D reconstruction tumors. Thus, accuracy three-dimensional further improved. Experiments show that local texture features obtained proposed similar those laser scanning. improved using U-Net 0.9851 obtained. approach significantly enhances precision boosts efficiency classification.