scholarly journals A medical image-based computer-aided diagnosis system for musculoskeletal disease and disorder.

2012 ◽  
Author(s):  
Tong Kuan. Chuah
Keyword(s):  
Medical Image ◽  
Computer Aided Diagnosis ◽  
Musculoskeletal Disease ◽  
Diagnosis System ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals An Orthopedic Auxiliary Diagnosis System Based on Image Recognition Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yang Guo ◽  
Chen Chen
Keyword(s):  
Image Registration ◽  
Medical Image ◽  
Computer Aided Diagnosis ◽  
Cartilage Tissue ◽  
Two Dimensional ◽  
Registration Method ◽  
Diagnosis System ◽  
Computer Aided ◽  
Orthopedic Diseases ◽  
Aided Diagnosis

There are many kinds of orthopedic diseases with complex professional background, and it is easy to miss diagnosis and misdiagnosis. The computer-aided diagnosis system of orthopedic diseases based on the key technology of medical image processing can locate and display the lesion location area by visualization, measuring and providing disease diagnosis indexes. It is of great significance to assist orthopedic doctors to diagnose orthopedic diseases from the perspective of visual vision and quantitative indicators, which can improve the diagnosis rate and accuracy of orthopedic diseases, reduce the pain of patients, and shorten the treatment time of diseases. To solve the problem of possible spatial inconsistency of medical images of orthopedic diseases, we propose an image registration method based on volume feature point selection and Powell. Through the linear search strategy of golden section method and Powell algorithm optimization, the best spatial transformation parameters are found, which maximizes the normalized mutual information between images to be registered, thus ensuring the consistency of two-dimensional spatial positions. According to the proposed algorithm, a computer-aided diagnosis system of orthopedic diseases is developed and designed independently. The system consists of five modules, which can complete many functions such as medical image input and output, algorithm processing, and effect display. The experimental results show that the system developed in this paper has good results in cartilage tissue segmentation, bone and urate agglomeration segmentation, urate agglomeration artifact removal, two-dimensional and three-dimensional image registration, and visualization. The system can be applied to clinical gout and cartilage defect diagnosis and evaluation, providing sufficient basis to assist doctors in making diagnosis decisions.

An automatic Computer-Aided Diagnosis system based on the Multimodal fusion of Breast Cancer (MF-CAD)

2021 ◽  
Vol 69 ◽  
pp. 102914
Author(s):  
Raouia Mokni ◽  
Norhene Gargouri ◽  
Alima Damak ◽  
Dorra Sellami ◽  
Wiem Feki ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Computer Aided Diagnosis ◽  
Multimodal Fusion ◽  
Diagnosis System ◽  
Automatic Computer ◽  
Computer Aided ◽  
Aided Diagnosis
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