Measurements of texture features of medical images and its application to computer-aided diagnosis in cardiomyopathy

Measurement ◽  
2005 ◽  
Vol 37 (3) ◽  
pp. 284-292 ◽  
Author(s):  
Du-Yih Tsai ◽  
Katsuyuki Kojima
Keyword(s):  
Medical Images ◽  
Texture Features ◽  
Computer Aided Diagnosis ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals Segmentation and Classification of Breast Cancer Tumour

2018 ◽  
Vol 2 (1) ◽  
pp. 14-18
Author(s):  
Gokalp Cinarer ◽  
Bulent Gursel Emiroglu ◽  
Ahmet Hasim Yurttakal
Keyword(s):  
Breast Cancer ◽  
Texture Features ◽  
Computer Aided Diagnosis ◽  
Wavelet Approximation ◽  
Proposed Model ◽  
Svm Algorithm ◽  
Computer Aided ◽  
Magnetic Resonance Imaging Mri ◽  
Aided Diagnosis

Breast cancer is cancer that forms in the cells of the breasts. Breast cancer is the most common cancer diagnosed in women in the world. Breast cancer can occur in both men and women, but it's far more common in women. Early detection of breast cancer tumours is crucial in the treatment. In this study, we presented a computer aided diagnosis expectation maximization segmentation and co-occurrence texture features from wavelet approximation tumour image of each slice and evaluated the performance of SVM Algorithm. We tested the model on 50 patients, among them, 25 are benign and 25 malign. The 80% of the images are allocated for training and 20% of images reserved for testing. The proposed model classified 2 patients correctly with success rate of 80% in case of 5 Fold Cross-Validation  Keywords: Breast Cancer, Computer-Aided Diagnosis (CAD), Magnetic Resonance Imaging (MRI);

Realization methods of computer-aided diagnosis system of medical images

2019 ◽  
Vol 13 ◽  
Author(s):  
Muhammad Aqeel Ashraf ◽  
Shahreen Kasim
Keyword(s):  
Data Model ◽  
Object Segmentation ◽  
Medical Images ◽  
Computer Aided Diagnosis ◽  
Support Vector ◽  
Cad System ◽  
Existing Problems ◽  
Vector Machines ◽  
Computer Aided ◽  
Aided Diagnosis

: In this paper, medical images are used to realize the computer-aided diagnosis (CAD) system which develops targeted solutions to existing problems. Relying on the Mi COM platform, this system has collected and collated cases of all kinds, based on which a unified data model is constructed according to the gold standard derived by deducting each instance. Afterwards, the object segmentation algorithm is employed to segment the diseased tissues. Edge modification and feature extraction are performed for the tissue block segmented. The features extracted are classified by applying support vector machines or the Naive Bayesian classification algorithm. From the simulation results, the CAD system developed in this paper allows realization of diagnosis and treatment and sharing of data resources.

Computer-Aided Diagnosis of Soft-Tissue Tumors Using Sonographic Morphologic and Texture Features

2009 ◽  
Vol 16 (12) ◽  
pp. 1531-1538 ◽  
Author(s):  
Chih-Yen Chen ◽  
Hong-Jen Chiou ◽  
Szu-Yuan Chou ◽  
See-Ying Chiou ◽  
Hsin-Kai Wang ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Texture Features ◽  
Soft Tissue Tumors ◽  
Computer Aided Diagnosis ◽  
Computer Aided ◽  
Aided Diagnosis
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