Master of Science

Mohammad Khatami

Mitarbeiter AG Schultz

Endenicher Allee 19A, Raum
D-53115 Bonn
Germany

2.110

Telefon:	+49 (0) 228 73-69142
Fax:	+49 (0) 228 73-4212
E-Mail:	khatami@REMOVETHISPART.cs.uni-bonn.de

Mohammad Khatami received a B.Sc. degree in the field of Information Technology Engineering from Azad University, Iran in 2009 and a M.Sc. in Media Informatics from RWTH-Aachen University in 2016. Starting in 2013, he has been working in the Visualization and Medical Image Analysis Group as a student research assistant. After finishing his Master thesis with the title "BundleMAP: Anatomically Localized Classification, Regression, and Hypothesis Testing in Diffusion MRI", he is now working in the same group as a teaching and research assistant.

Veranstaltungen

Publikationen

		CoBundleMAP: Consistent 2D Parameterization Of Fiber Bundles Across Subjects and Hemispheres Mohammad Khatami, Regina Wehler und Thomas Schultz In proceedings of IEEE Int'l Symposium on Biomedical Imaging, pages 1475-1478, 2019 [Details] [Paper] [Bibtex]

		Open-Box Training of Kernel Support Vector Machines: Opportunities and Limitations Mohammad Khatami und Thomas Schultz In proceedings of Vision, Modeling & Visualization, pages 63-72, 2019 [Details] [Paper] [Bibtex]

		A Bag-of-Features Approach to Predicting TMS Language Mapping Results from DSI Tractography Mohammad Khatami, Katrin Sakreida, Georg Neuloh und Thomas Schultz In proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI), Springer, 2017 [Details] [Paper] [Bibtex]

		BundleMAP: Anatomically Localized Classification, Regression, and Hypothesis Testing in Diffusion MRI Mohammad Khatami, Tobias Schmidt-Wilcke, Pia C. Sundgren, Amin Abbasloo, Bernhard Schölkopf und Thomas Schultz In: Pattern Recognition (2017), 63(593-600) [Details] [Paper] [Bibtex]

		BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease Mohammad Khatami, Tobias Schmidt-Wilcke, Pia C. Sundgren, Amin Abbasloo, Bernhard Schölkopf und Thomas Schultz In proceedings of Int'l Workshop on Machine Learning in Medical Imaging (MLMI), pages 52-60, Springer, 2015 [Details] [Paper] [Bibtex]