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Academic Appointments


  • Consulting Assistant Professor, Psychiatry and Behavioral Sciences

Teaching

Postdoctoral Advisees


Publications

Journal Articles


  • White matter microstructural recovery with abstinence and decline with relapse in alcohol dependence interacts with normal ageing: a controlled longitudinal DTI study LANCET PSYCHIATRY Pfefferbaum, A., Rosenbloom, M. J., Chu, W., Sassoon, S. A., Rohlfing, T., Pohl, K. M., Zahr, N. M., Sullivan, E. V. 2014; 1 (3): 202-212
  • Regional Manifold Learning for Disease Classification IEEE TRANSACTIONS ON MEDICAL IMAGING Ye, D. H., Desjardins, B., Hamm, J., Litt, H., Pohl, K. M. 2014; 33 (6): 1236-1247
  • PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration IEEE TRANSACTIONS ON MEDICAL IMAGING Kwon, D., Niethammer, M., Akbari, H., Bilello, M., Davatzikos, C., Pohl, K. M. 2014; 33 (3): 651-667

    Abstract

    We propose a new method for deformable registration of pre-operative and post-recurrence brain MR scans of glioma patients. Performing this type of intra-subject registration is challenging as tumor, resection, recurrence, and edema cause large deformations, missing correspondences, and inconsistent intensity profiles between the scans. To address this challenging task, our method, called PORTR, explicitly accounts for pathological information. It segments tumor, resection cavity, and recurrence based on models specific to each scan. PORTR then uses the resulting maps to exclude pathological regions from the image-based correspondence term while simultaneously measuring the overlap between the aligned tumor and resection cavity. Embedded into a symmetric registration framework, we determine the optimal solution by taking advantage of both discrete and continuous search methods. We apply our method to scans of 24 glioma patients. Both quantitative and qualitative analysis of the results clearly show that our method is superior to other state-of-the-art approaches.

    View details for DOI 10.1109/TMI.2013.2293478

    View details for Web of Science ID 000332599500005

    View details for PubMedID 24595340

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