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A Medical Software System for Volumetric Analysis of Cerebral Pathologies in Magnetic Resonance Imaging (MRI) Data

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Abstract

In this contribution, a medical software system for volumetric analysis of different cerebral pathologies in magnetic resonance imaging (MRI) data is presented. The software system is based on a semi-automatic segmentation algorithm and helps to overcome the time-consuming process of volume determination during monitoring of a patient. After imaging, the parameter settings—including a seed point—are set up in the system and an automatic segmentation is performed by a novel graph-based approach. Manually reviewing the result leads to reseeding, adding seed points or an automatic surface mesh generation. The mesh is saved for monitoring the patient and for comparisons with follow-up scans. Based on the mesh, the system performs a voxelization and volume calculation, which leads to diagnosis and therefore further treatment decisions. The overall system has been tested with different cerebral pathologies—glioblastoma multiforme, pituitary adenomas and cerebral aneurysms– and evaluated against manual expert segmentations using the Dice Similarity Coefficient (DSC). Additionally, intra-physician segmentations have been performed to provide a quality measure for the presented system.

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Acknowledgements

First of all the authors want to thank all reviewers for their thoughtful comments. The authors would also like to thank the physicians Dr. Daniela Kuhnt, Dr. Malgorzata Kolodziej, Dr. Barbara Carl and Christoph Kappus for (a) performing the manual segmentations of the medical images and therefore providing the ground truth for the evaluation and (b) helping with the medical introduction. Furthermore, the authors would like to thank Fraunhofer MeVis in Bremen, Germany, for their collaboration and especially Prof. Dr. Horst K. Hahn for his support.

Conflict of interest statement

All authors in this paper have no potential conflict of interests.

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Authors and Affiliations

  1. Department of Neurosurgery, University of Marburg, Baldingerstraße, 35043, Marburg, Germany

    Jan Egger, Christoph Kappus & Christopher Nimsky

  2. Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Str, 35032, Marburg, Germany

    Jan Egger & Bernd Freisleben

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  1. Jan Egger
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Correspondence to Jan Egger.

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Egger, J., Kappus, C., Freisleben, B. et al. A Medical Software System for Volumetric Analysis of Cerebral Pathologies in Magnetic Resonance Imaging (MRI) Data. J Med Syst 36, 2097–2109 (2012). https://doi.org/10.1007/s10916-011-9673-6

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