Image processing system based on tumor imaging omics
By improving the multi-scale feature frequency domain decomposition filtering algorithm, adaptively determining the image fusion weights, the problem of insufficient universality and flexibility of the existing traditional Chinese medicine image fusion algorithm is solved, and the fusion effect of multimodal tumor examination images and the teaching effect of medical teaching is improved.
CN119722667AActive Publication Date: 2025-03-28SHANDONG PROVINCIAL HOSPITAL AFFILIATED TO SHANDONG FIRST MEDICAL UNIVERSITY (SHANDONG PROVINCIAL HOSPITAL)
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Patent Information
- Application Number
- CN202510220222.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-27
- Publication Date
- 2025-03-28
- Estimated Expiration
- 2045-02-27
AI Technical Summary
Technical Problem
In the prior art, the medical image fusion algorithm based on multi-scale feature frequency domain decomposition filtering is poor in universality and flexibility, resulting in poor image fusion effect of multimodal tumor examination and affecting the teaching effect of medical teaching.
Method used
By improving the existing algorithm, the fusion weights of different feature image layers are determined, and the adaptive image fusion method is adopted, and image fusion is combined with multi-scale feature frequency domain decomposition filtering.
Benefits of technology
It improves the universality and flexibility of fusion images, enhances the effect of image fusion, and makes the application of final fusion images more accurate and effective in medical teaching.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention relates to the technical field of image fusion, in particular to an image processing system based on tumor imageomics, which improves an existing medical image fusion algorithm based on multi-scale characteristic frequency domain decomposition filtering, and after a fusion layering with a better representation effect on graphic information and focus information after first fusion is determined, the fusion layering is carried out on the image information and the focus information; and according to the image feature expression of the fusion layer and the focus feature expression, adaptively determining the fusion weight of image fusion of different feature image layers, thereby performing adaptive image fusion based on the adaptive fusion weight. The problem that a medical image fusion algorithm based on multi-scale characteristic frequency domain decomposition filtering is poor in universality and flexibility is solved, and the universality and flexibility of the obtained final fusion image are better and more accurate.
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