Knowledge Propagation Models for Image Registration Scientific Director: Nassir Navab Contact Person(s): Amin Katouzian , Tingying Peng, Sailesh Conjeti,

Keywords: Registration / Visualization, Medical Imaging, Machine Learning for Medical Applications, Microscopic Image Analysis

Abstract

To register modalities with complex intensity relationships, we leverage machine learning algorithm to cast it into a mono modal registration problem. This is done by extracting tissue specific features for propagating anatomical/structural knowledge from one modalitiy to an other through an online learnt propagation model. The registration and propagation steps are iteratively performed and refined. For proof-of-concept, we employ it for registering (1) Immunofluorescence to Histology images and (2) Intravascular Ultrasound to Histology Images.

Team

Contact Person(s)

Dr. Amin Katouzian

Dr. Sailesh Conjeti

Dr. Tingying Peng

Working Group

Dr. Amin Katouzian

Debdoot Sheet

Dr. Mehmet Yigitsoy

Prof. Dr. Nassir Navab

Dr. Sailesh Conjeti

Dr. Tingying Peng

Location

Technische Universität München Institut für Informatik / I16 Boltzmannstr. 3 85748 Garching bei München Tel.: +49 89 289-17058 Fax: +49 89 289-17059

Visit our lab at Garching.

Klinikum rechts der Isar der Technischen Universitüt München Ismaninger Str. 22 81675 München IFL Lab - Room: 01.3a-c Tel.: +49 89 4140-6457 Fax: +49 89 4140-6458

Visit our lab at Klinikum rechts der Isar.



internal project page

Please contact Amin Katouzian , Tingying Peng, Sailesh Conjeti, for available student projects within this research project.