We present a nearly automatic graph-based segmentation method for patient specific modeling of the aortic arch and carotid arteries from CTA scans for interventional radiology simulation. The method starts with morphological-based segmentation of the aorta and the construction of a prior intensity probability distribution function for arteries. The carotid arteries are then segmented with a graph min-cut method based on a new edge weights function that adaptively couples the voxel intensity, the intensity prior, and geometric vesselness shape prior. Finally, the same graph-cut optimization framework is used for nearly automatic removal of a few vessel segments and to fill minor vessel discontinuities due to highly significant imaging artifacts. Our method accurately segments the aortic arch, the left and right subclavian arteries, and the common, internal, and external carotids and their secondary vessels. It does not require any user initialization, parameters adjustments, and is relatively fast (150-470 secs). Comparative experimental results on 30 carotid arteries from 15 CTAs from two medical centres manually segmented by expert radiologist yield a mean symmetric surface distance of 0.79mm (std=0.25mm). The nearly automatic refinement requires about 10 seed points and took less than 2mins of treating physician interaction with no technical support for each case.
|Original language||American English|
|Title of host publication||Modelling the Physiological Human - 3D Physiological Human Workshop, 3DPH 2009, Proceedings|
|Number of pages||12|
|State||Published - 2009|
|Event||Workshop on 3D Physiological Human 2009, 3DPH 2009 - Zermatt, Switzerland|
Duration: 29 Nov 2009 → 2 Dec 2009
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||Workshop on 3D Physiological Human 2009, 3DPH 2009|
|Period||29/11/09 → 2/12/09|
Bibliographical noteFunding Information:
We are grateful to Mr D R Millar, consultant obstetrician; Mrs Bullas and the staff of the medical records department at the Jessop Hospital for Women who preserved the records and allowed us to use them; and to the staff at NHS central registry and OPCS who traced the men. The study was supported by a grant from the Wellcome Trust.