University of Heidelberg
Faculty of Medicine Mannheim
University Hospital Mannheim
CKM receives DFG funding for Project "Prdiktion von Therapieansprechen und Outcome beim lokal fortgeschrittenen Rektum-Karzinom mittels Radiomics und Deep Learning: eine beispielhafte Anwendung fr eine allgemein verwendbare, Deep Learning basierte Prozessierungs-Pipeline fr die Bild-Klassifikation" read more.
Alena-Kathrin Schnurr presented on our research on AI in medical imaging @ Research Plus forum
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Dr. Mathias Davids wins the I. I. Rabi Award of the International Society for Magnetic Resonance in Medicine (ISMRM),
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Multimodal image registration of pre- and intra-interventional data for surgical planning of transarterial chemoembolisation

B. Waldkirch, S. Engelhardt, F. Zöllner, L. Schad and I. Wolf

Proc. SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 10951, p.109512U

Multimodal registration improves surgical planning and the performance of interventional procedures such as transarterial chemoembolizations (TACE), since it allows to combine complementary information provided by pre- and intrainterventional data about tumor localization and access. However, no registration methods specifically developed for the multimodal registration of abdominal scans exist and as a result only general-purpose methods are available for this application. In this paper, we evaluate and optimize the performance of three standard registration methods which rely on different similarity metrics, namely Advanced Mattes Mutual Information (AMMI), Advanced Normalized Correlation (ANC) and Normalized Mutual Information (NMI), for the registration of preinterventional T1- and T2-weighted MRI to preinterventional CT as well as intrainterventional Cone Beam CT (CBCT) to preinterventional CT of the liver. Moreover, different variants of the registration algorithms, based on the introduction of masks and different resolution levels in multistage registrations, are investigated. To evaluate the performance of each registration method, the capture range was estimated based on the calculation of the mean target registration error.

Contact: Prof. Dr. Frank Zöllner last modified: 21.09.2020
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