Kwame Kutten

Kwame Kutten, PhD


Office: Clark 104C


PhD, Biomedical Engineering, Johns Hopkins University, 2017
BS, Biomedical Engineering, Rensselaer Polytechnic Institute, 2009

Research Interests

Kwame Sanwu Kutten is a lecturer in the Department of Biomedical Engineering at Johns Hopkins University. He is an instructor in the Gateway Computing course and provides daily support for students in quantitative classes within the department. His research combines biomedical imaging and computational methods to study how brain structure and connections change in disorder and disease.

Publications Search

From Pub Med   |   Google Scholar Profile

Selected Publications

X. Li, L. Chen, K. Kutten, C. Ceritoglu, Y. Li, N. Kang, J. T. Hsu, Y. Qiao, H. Wei, C. Liu, M. I. Miller, S. Mori, D. M. Yousem, P. C. van Zijl, and A. V. Faria, “Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility,” NeuroImage, vol. 191, pp. 337–349, 2019.

K. S. Kutten, N. Charon, M. I. Miller, J. T. Ratnanather, J. Matelsky, A. D. Baden, K. Lillaney, K. Deisseroth, L. Ye, and J. T. Vogelstein, “A large deformation diffeomorphic approach to registration of CLARITY images via mutual information,” in Medical Image Computing and Computer Assisted Intervention – MICCAI 2017 (M. Descoteaux, L. Maier-Hein, A. Franz, P. Jannin, D. L. Collins, and S. Duchesne, eds.), vol. 10433 of Lecture Notes in Computer Science, pp. 275–282, 2017.

K. S. Kutten, S. M. Eacker, V. L. Dawson, T. M. Dawson, J. T. Ratnanather, and M. I. Miller, “An image registration pipeline for analysis of transsynaptic tracing in mice,” in Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging (B. Gimi and A. Krol, eds.), 2016.

X. Tang, K. Kutten, C. Ceritoglu, S. Mori, and M. I. Miller, “Simultaneous skull-stripping and lateral ventricle segmentation via fast multi-atlas likelihood fusion,” in Proc. SPIE 9413: Medical Imaging 2015: Image Processing (S. Ourselin and M. A. Styner, eds.), 2015.

H. Wen, K. A. Marsolo, E. E. Bennett, K. S. Kutten, R. P. Lewis, D. B. Lipps, N. D. Epstein, J. F. Plehn, and P. Croisille, “Adaptive postprocessing techniques for myocardial tissue tracking with displacement-encoded MR imaging,” Radiology, vol. 246, no. 1, 2008.