3D segmentation of coronary arteries based on advanced mathematical morphology techniques

Bessem Bouraoui 1, 2 Christian Ronse 1 Joseph Baruthio 2 Nicolas Passat 1 Philippe Germain 3
1 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
2 LINC - Laboratoire d'Imagerie et de Neurosciences Cognitives
3 Service de Radiologie A, Nouvel Hôpital Civil
Abstract : In this article, we propose an automatic algorithm for coronary artery segmentation from 3D X-ray data sequences of a cardiac cycle (3D-CT scan, 64 detectors, 10 phases). This method is based on recent mathematical morphology techniques (some of them being extended in this article). It is also guided by anatomical knowledge, using discrete geometric tools to fit on the artery shape independently from any perturbation of the data. The application of the method on a validation dataset (60 images: 20 patients in 3 phases) led to 90% correct (and automatically obtained) segmentations, the 10% remaining cases corresponding to images where the SNR was very low.
Keywords : segmentation hit-or-miss transform region-growing coronary arteries
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Bessem Bouraoui, Christian Ronse, Joseph Baruthio, Nicolas Passat, Philippe Germain. 3D segmentation of coronary arteries based on advanced mathematical morphology techniques. Computerized Medical Imaging and Graphics, Elsevier, 2010, 34 (5), pp.377-387. ⟨10.1016/j.compmedimag.2010.01.001⟩. ⟨hal-01694412⟩

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