Vanderbilt University
Institute of Imaging Science

Anita Mahadevan-Jansen, Ph.D.

Professor of Biomedical Engineering and Neurological Surgery

Contact Information
(615) 343-4787


I am interested in biomedical Image and signal processing, combined with different machine learning techniques to aid in clinical diagnosis and treatment procedures of various diseases.


At VUIIS, I am trying to analyze the intrinsic functional connectivity of the spinal cord of non-human primates, using the Local field Potential signal . In particular, I am trying to do data-driven analysis for analyzing the intrinsic functional connectivity of the spinal cord. Also, in another project I am involved in applying machine learning methods to differentiate between different stages of Alzeihmer's using White matter resting state connectivity obtained using fMRI.


A Sengupta, S Agarwal, PK Gupta, S Ahlawat, R Patir, RK Gupta, A Singh. On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI.European journal of radiology 106, 199-20

A Sengupta, RK Gupta, A Singh.Evaluation of B 1 inhomogeneity effect on DCE-MRI data analysis of brain tumor patients at 3T.Journal of translational medicine 15 (1), 242

Anirban Sengupta, Anandh K. Ramaniharan,Rakesh K Gupta, Sumeet Agarwal.Glioma Grading Using a Machine?Learning Framework Based on Optimized Features Obtained From T1 Perfusion MRI and Volumes of Tumor Components. Journal of Magnetic Resonance Imaging.

Sengupta A, Sahoo P, Gupta P, Gupta RK, Singh A. T1 mapping using 3-point FSE and multi-flip-angle methods and effect of B1 field inhomogeneity on T1 in human brain on 3T MRI scanner. ESMRMB Annual Scientific Meeting 2016, Vienna. PN-202

Sengupta A, Gupta RK, Agarwal S and Singh A. A Machine Learning Based Approach for Fast T1 estimation with Improved Accuracy. ISMRM: 25th Annual Meeting & Exhibition-2017, Honolulu, USA, (Proc.Intl.Soc.Mag.Reson.Med. 25(2017), Page Nu-3994).