Preconditioned intensity-based prostate registration using statistical deformation models

Despite the common invisibility of cancerous lesions in transrectal 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 accur...

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Bibliographic Details
Published in2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) pp. 853 - 857
Main Authors Zettinig, Oliver, Rackerseder, Julia, Lentes, Beatrice, Maurer, Tobias, Westenfelder, Kay, Eiber, Matthias, Frisch, Benjamin, Navab, Nassir
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2017
Subjects
Biological system modeling
Biopsy
Deformable models
Lesions
Magnetic resonance imaging
Measurement
Preconditioning
Prostate
Registration
Statistical Deformation Model
Ultrasonic imaging
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Summary:Despite the common invisibility of cancerous lesions in transrectal 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 1.41 mm in the vicinity of suspicious areas.
ISSN:1945-8452
DOI:10.1109/ISBI.2017.7950651