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Proceedings Paper

Navigation-supported diagnosis of the substantia nigra by matching midbrain sonography and MRI
Author(s): Zein Salah; David Weise; Bernhard Preim; Joseph Classen; Georg Rose
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Paper Abstract

Transcranial sonography (TCS) is a well-established neuroimaging technique that allows for visualizing several brainstem structures, including the substantia nigra, and helps for the diagnosis and differential diagnosis of various movement disorders, especially in Parkinsonian syndromes. However, proximate brainstem anatomy can hardly be recognized due to the limited image quality of B-scans. In this paper, a visualization system for the diagnosis of the substantia nigra is presented, which utilizes neuronavigated TCS to reconstruct tomographical slices from registered MRI datasets and visualizes them simultaneously with corresponding TCS planes in realtime. To generate MRI tomographical slices, the tracking data of the calibrated ultrasound probe are passed to an optimized slicing algorithm, which computes cross sections at arbitrary positions and orientations from the registered MRI dataset. The extracted MRI cross sections are finally fused with the region of interest from the ultrasound image. The system allows for the computation and visualization of slices at a near real-time rate. Primary tests of the system show an added value to the pure sonographic imaging. The system also allows for reconstructing volumetric (3D) ultrasonic data of the region of interest, and thus contributes to enhancing the diagnostic yield of midbrain sonography.

Paper Details

Date Published: 23 February 2012
PDF: 8 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83153G (23 February 2012); doi: 10.1117/12.911383
Show Author Affiliations
Zein Salah, Univ. Magdeburg (Germany)
David Weise, Univ. Leipzig (Germany)
Bernhard Preim, Univ. Magdeburg (Germany)
Joseph Classen, Univ. Leipzig (Germany)
Georg Rose, Univ. Magdeburg (Germany)

Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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