A Shape-based Statistical Method to Retrieve 2D TRUS-MR Slice Correspondence for Prostate Biopsy

Jhimli Mitra 1, * Abhilash Srikantha 1 Désiré Sidibé 1 Robert Marti 2 Arnau Oliver 2 Xavier Llado 2 Soumya Ghose 1 Joan Vilanova 2 Josep Comet 2 Fabrice Mériaudeau 1
* Auteur correspondant
1 Le2i - Laboratoire Electronique, Informatique et Image [UMR6303]
2 VICOROB - Visio per computador i robotica
Abstract : This paper presents a method based on shape-context and statistical measures to match interventional 2D Trans Rectal Ultrasound (TRUS) slice during prostate biopsy to a 2D Magnetic Resonance (MR) slice of a pre-acquired prostate volume. Accurate biopsy tissue sampling requires translation of the MR slice information on the TRUS guided biopsy slice. However, this translation or fusion requires the knowledge of the spatial position of the TRUS slice and this is only possible with the use of an electro-magnetic (EM) tracker attached to the TRUS probe. Since, the use of EM tracker is not common in clinical practice and 3D TRUS is not used during biopsy, we propose to perform an analysis based on shape and information theory to reach close enough to the actual MR slice as validated by experts. The Bhattacharyya distance is used to find point correspondences between shape-context representations of the prostate contours. Thereafter, Chi-square distance is used to find out those MR slices where the prostates closely match with that of the TRUS slice. Normalized Mutual Information (NMI) values of the TRUS slice with each of the axial MR slices are computed after rigid alignment and consecutively a strategic elimination based on a set of rules between the Chi-square distances and the NMI leads to the required MR slice. We validated our method for TRUS axial slices of 15 patients, of which 11 results matched at least one experts validation and the remaining 4 are at most one slice away from the expert validations.
Keywords : normalized mutual information Prostate biopsy 2D TRUS/3D MR correspondence shape-context normalized mutual information.
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Communication dans un congrès
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Contributeur : Désiré Sidibé <>
Soumis le : vendredi 9 mars 2012 - 09:24:42
Dernière modification le : mercredi 12 septembre 2018 - 01:27:03
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Jhimli Mitra, Abhilash Srikantha, Désiré Sidibé, Robert Marti, Arnau Oliver, et al.. A Shape-based Statistical Method to Retrieve 2D TRUS-MR Slice Correspondence for Prostate Biopsy. SPIE Medical Imaging, Feb 2012, San Diego, United States. pp.1-9. ⟨hal-00658088⟩

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