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Personnel

Axel WismüllerAxel W. E. Wismüller, M.D., Ph.D
Principal Investigator
MCA 2-2-214
Phone: (585) 276-1323
axel_wismueller@urmc.rochester.edu

Intelligent image acquisition and analysis systems in biomedicine

Mahesh NagarajanMahesh B. Nagarajan, Ph.D.
Postdoctoral Fellow
mahesh.nagarajan@rochester.edu

A Framework for Computer-Aided Diagnosis with Novel Computational Methods for Characterizing Healthy and Pathological Soft Tissue Patterns on Medical Images

Anas AbidinAnas Zainul Abidin, M.S.
Graduate Student
anas.abidin@rochester.edu

Novel methods for image/time series analysis with focus on developing novel biomarkers for neurological disorders

Walter ChecefskyWalter Checefsky
Graduate Student
walter_checefsky@urmc.rochester.edu

Characterization of trabecular bone structure on quantitative CT to compliment conventional DXA-derived measures of bone mineral density for improved fracture risk estimation.

Udaysankar ChockanathanUdaysankar Chockanathan
Graduate Student
udaysankar_chockanathan@urmc.rochester.edu

Comparison of the efficacy of various correlation and causation algorithms for quantifying interactions in resting-state fMRI brain activity using graph theory approaches

Botao DengBotao Deng, M.S.
Graduate Student
bdeng3@ur.rochester.edu

Applying deep learning techniques to classify lung disorders in clinical imaging.

Adora DSouzaAdora Melissa DSouza, M.S.
Graduate Student
adora.dsouza@rochester.edu

Evaluation of different non-metric clustering methods for visualization of functional connectivity in the human brain on functional MRI

Raul RodriguezRaul Rodriguez
Graduate Student

Parallelization of 3D visualization of large-scale functional integration in the human brain on resting-state fMRI data, using effective connectivity analysis and non-metric clustering, by means of Graphics Processing Units (GPUs)

Xixi WangXixi Wang, M.S.
Graduate Student
xixi.wang@rochester.edu

Investigating the use of mutual information and non-metric clustering for functional connectivity analysis on resting state fMRI