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Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

O. Zettinig, J. Rackerseder, B. Lentes, T. Maurer, K. Westenfelder, M. Eiber, B. Frisch, N. Navab
Preconditioned Intensity-Based Prostate Registration using Statistical Deformation Models
IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, April 2017. (bib)

Despite the common invisibility of cancerous lesions in trans-rectal ultrasound (TRUS), TRUS-guided random biopsy is considered the gold standard to diagnose prostate cancer. Pre-interventional magnetic resonance imaging (MRI) has been shown to improve the detection of malignancies but fast and accurate MRI/TRUS registration for multi-modal biopsy guidance remains challenging. In this work, we derive a statistical deformation model (SDM) from 50 automatically segmented patient datasets and propose a novel registration scheme based on a lesion-specific, anisotropic preconditioned similarity metric. The approach is validated on a dataset of 10 patients, showing landmark registration errors of 1.41mm in the vicinity of suspicious areas.
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