scholarly journals Implementation of Computer Aided Diagnosis System Based on Parallel Approach of Ant Based Medical Image Segmentation

2011 ◽  
Vol 7 (2) ◽  
pp. 291-297 ◽  
Author(s):  
Jaya
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Computer Aided Diagnosis ◽  
Medical Image Segmentation ◽  
Diagnosis System ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals An effective approach for CT lung segmentation using region growing

2021 ◽  
Vol 2082 (1) ◽  
pp. 012001
Author(s):  
Xi Yang ◽  
Guanyu Xu ◽  
Teng Zhou
Keyword(s):  
Medical Image ◽  
Lung Diseases ◽  
Region Growing ◽  
Computer Aided Diagnosis ◽  
Medical Image Segmentation ◽  
Point Selection ◽  
Seed Point ◽  
Lung Segmentation ◽  
Computer Aided ◽  
Aided Diagnosis

Abstract X-ray is an important means of detecting lung diseases. With the increasing incidence of lung diseases, computer-aided diagnosis technology is of great significance in clinical treatment. It has become a hot research direction to use computer-aided diagnosis to recognize chest radiography images, which can alleviate the uneven status of regional medical level. For clinical diagnosis, medical image segmentation can enable users to timely obtain the target region they are interested in and analyze it, which is significant to be used as an important basis for auxiliary research and judgment. In this case, a region growing algorithm based on threshold presegmentation is selected for lung segmentation, which integrates image enhancement, threshold segmentation, seed point selection and morphological post-processing, etc., to improve the segmentation effect, which also has certain reference value for other medical image processing.

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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