The week's pick
Reseach Article
Disease Detection in MRS (Magnetic Resonance Spectroscopy)
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 178 - Number 1 |
| Year of Publication: 2017 |
| Authors: Shivam Thakur, Sanket Patole, S. K. Pathan |
10.5120/ijca2017915719
|
Shivam Thakur, Sanket Patole, S. K. Pathan . Disease Detection in MRS (Magnetic Resonance Spectroscopy). International Journal of Computer Applications. 178, 1 ( Nov 2017), 33-35. DOI=10.5120/ijca2017915719
Abstract
Magnetic resonance spectroscopy is a technique for imaging modality used for the metabolite detection in the various parts of our body (e.g. Kidney, prostate, kidney, heart, muscle, brain) for any human being suffering from different types of disorders. It provides us the valuable information for the therapeutic monitoring of a patient as well as any diagnosis. Over the period there has been a huge amount of progress in the MRS signal processing techniques for neurometabolites quantization. This paper presents the idea of developing a software which could be helpful to the medical experts in obtaining a classified study about diseases like brain tumor, migraine, Alzheimer’s etc. with the help of magnetic resonance spectroscopy and machine learning algorithms like ID3 and Bayesian Probability. The software could easily detect the changes in the behavior of metabolites and their required functions. It will use history of patient data as training set for the application to learn on and predict the most accurate dis-ease in the future.
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