Diagnosis of Brain Lesions, Glioma, Multiple-Sclerosis and Metastases from MRI: An efficient classifier-aided method using Refractive Index as a surrogate Biological Marker

Authors

DOI:

https://doi.org/10.14738/jbemi.53.4700

Keywords:

Medical Imaging, Biomedical Engineering, Machine Learning, Brain Lesions, Glioma, Spectroscopy,

Abstract

We introduce a highly accurate method of diagnosing the various pathological conditions that might exist in a subject’s brain, like edema, multiple sclerosis (Tumefactive, Relapsing-remitting, secondary-progressive, primary-progressive and progressive-relapsing), glioma, glioblastoma and metastases. These show up on conventional MRI scans, but it is often difficult to identify the exact type of the pathology from the grayscale image. We employ the use of Support Vector Machines (SVM) to work on the MR Spectroscopy [6, 12] data and correctly identify the condition-especially in seemingly vague cases where radiologists cannot rule out high uncertainty in their conclusion. The SVM trains on data sets collected for different patients and optimizes its hyperplanes based on eight input variables – T2, CHO, ADC, CR, CHO/NAA, CR/NAA, LIP/LAC, MI, CH/CR, T2 periphery [6] and Refractive index. Refractive index is an additional parameter which we include to get better boundary lines and accuracy, as shown in our prior works [10]. We test this SVM on a set of 19 patients’ data and achieve 100% accuracy in predictions. The training and testing is carried out in MATLAB.

Author Biographies

Sparsh Jain, Jadavpur University

Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India

Tapan Krishna Biswas, (Former) Harvard University, Brigham and Women’s Hospital, Boston MA, United States of America

Department of Instrumentation and Electronics Engineering

Radiologist [M.D. , D.M.R.D.] and Research Scholar

Brigham and Women's Hospital (Harvard Medical) 

Research Fellow

Rajib Bandyopadhyay, Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India

Department of Instrumentation and Electronics Engineering

Professor

Former Head

References

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Published

2018-07-08

How to Cite

Jain, S., Biswas, T. K., & Bandyopadhyay, R. (2018). Diagnosis of Brain Lesions, Glioma, Multiple-Sclerosis and Metastases from MRI: An efficient classifier-aided method using Refractive Index as a surrogate Biological Marker. Journal of Biomedical Engineering and Medical Imaging, 5(3), 19. https://doi.org/10.14738/jbemi.53.4700