Blood vessels 3D rendering has numerous applications, ranging from diagnosis to pre-procedural and surgical approaches as it enriches vessels visualization for the clinician. In this paper, we propose a 3D blood vessels segmentation method designed for use with a cone beam computed tomography (CBCT). The algorithm constitutes a module in the development of an angio-CT visualization system, based on augmented or virtual reality as instruments supporting and improving medical decisions. The proposed segmentation tool exploits a bone segmentation step for easing the extraction of blood vessels. Both steps are based on region growing technique. For each subject are used two CBCT acquisitions, where the first one is acquired with a traditional CT scan and is used for bone extraction, while the second one is acquired after contrast medium administration and is used for vessels reconstruction. This novel segmentation algorithm provides an automatic and accurate tool to segment and render blood vessels tree. 3D anatomical models were viewed through a virtual reality environment in order to validate the visualization system.

3D Vessel Segmentation in CT for Augmented and Virtual Reality / Agnese Simoni, Eleonora Tiribilli, Cosimo Lorenzetto, Leonardo Manetti, Ernesto Iadanza, Leonardo Bocchi. - ELETTRONICO. - (2021), pp. 57-68. ((Intervento presentato al convegno MEFDATA 2020 [10.1007/978-3-030-72805-2_4].

3D Vessel Segmentation in CT for Augmented and Virtual Reality

Eleonora Tiribilli;Ernesto Iadanza;Leonardo Bocchi
2021

Abstract

Blood vessels 3D rendering has numerous applications, ranging from diagnosis to pre-procedural and surgical approaches as it enriches vessels visualization for the clinician. In this paper, we propose a 3D blood vessels segmentation method designed for use with a cone beam computed tomography (CBCT). The algorithm constitutes a module in the development of an angio-CT visualization system, based on augmented or virtual reality as instruments supporting and improving medical decisions. The proposed segmentation tool exploits a bone segmentation step for easing the extraction of blood vessels. Both steps are based on region growing technique. For each subject are used two CBCT acquisitions, where the first one is acquired with a traditional CT scan and is used for bone extraction, while the second one is acquired after contrast medium administration and is used for vessels reconstruction. This novel segmentation algorithm provides an automatic and accurate tool to segment and render blood vessels tree. 3D anatomical models were viewed through a virtual reality environment in order to validate the visualization system.
Mediterranean Forum–Data Science Conference: First International Conference, MeFDATA 2020, Sarajevo, Bosnia and Herzegovina, October 24, 2020, Revised Selected Papers
MEFDATA 2020
Goal 3: Good health and well-being
Agnese Simoni, Eleonora Tiribilli, Cosimo Lorenzetto, Leonardo Manetti, Ernesto Iadanza, Leonardo Bocchi
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2158/1237330
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