scholarly journals Semi-automatic Segmentation of MRI Brain Metastases Combining Support Vector Machine and Morphological Operators

2019 ◽  
Author(s):  
Gloria Gonella ◽  
Elisabetta Binaghi ◽  
Paola Nocera ◽  
Cinzia Mordacchini
Keyword(s):  
Support Vector Machine ◽  
Brain Metastases ◽  
Automatic Segmentation ◽  
Support Vector ◽  
Morphological Operators ◽  
Mri Brain

A Comparative Objective Assessment on Mesh-Based and SVM-Based 3D Reconstruction of MRI Brain

2019 ◽  
Vol 8 (3) ◽  
pp. 41-54
Author(s):  
Sushitha Susan Joseph ◽  
Aju D.
Keyword(s):  
Support Vector Machine ◽  
Three Dimensional ◽  
Disease Diagnosis ◽  
Two Dimensions ◽  
Support Vector ◽  
Brain Surgery ◽  
Three Dimensional Reconstruction ◽  
Advantages And Disadvantages ◽  
Mri Brain ◽  
Dimensional Reconstruction

Three-dimensional reconstruction is the process of acquiring the volumetric information from two dimensions, converting and representing it in three dimensions. The reconstructed images play a vital role in the disease diagnosis, treatment and surgery. Brain surgery is one of the main treatment options following the diagnosis of brain damage. The risk associated with brain surgery is high. Reconstructed brain images help the surgeons to visualize the exact location of tumor, plan and perform the surgical procedures from craniotomy to tumor resection with high precision. This survey provides an overview of the three-dimensional reconstruction techniques in MRI brain and brain tumors. The triangle generation methods and support vector machine methods are briefly described. The advantages and disadvantages of each method is discussed. The comparison reveals that Immune Sphere Shaped Support Vector Machine is the best choice when execution time is considered and triangle mesh generation algorithm is the best when visual quality is considered.

scholarly journals Classification of Brain MRI Tumor Images Using Fuzzy C Means Clustering With Firefly Algorithms Optimized Support Vector Machine

2021 ◽  
Vol 23 (11) ◽  
pp. 70-77
Author(s):  
M.R. Thiyagupriyadharsan ◽  
◽  
Dr.S. Suja ◽  
Keyword(s):  
Health Care ◽  
Support Vector Machine ◽  
Brain Tumor ◽  
Health Care System ◽  
Support Vector ◽  
Human Beings ◽  
Fuzzy C Means ◽  
Mri Brain ◽  
Care System

In the contemporary world, many dangerous disease which are affecting human beings and new pandemic disease is also raising alarm to have an effective health care system. In this aspect the technology plays a major role in improving and optimizing the health care system. The diagnostic is done by taking blood test, urine test, and medical imaging like X-ray, CT scan, Ultrasound scan and MRI scan system. Among these, the paper focus will be emphasized on MRI imaging in identifying the brain tumor using image processing. In the proposed work the fuzzy C means(FCM) algorithm along with firefly algorithm optimized support vector machine (SVM) are used to classify the MRI brain tumor images. The results of these works are compared using the performance metrics such as accuracy, sensitivity, specificity and precision. The proposed method gives best results for the classification of MRI brain tumor images.

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