Automatic vessel extraction of lower extremity CT angiography using multi-segmented volume and regional vessel tracking

Min Jin Lee; Helen Hong; Jin Wook Chung

doi:10.1117/12.2006685

13 March 2013 Automatic vessel extraction of lower extremity CT angiography using multi-segmented volume and regional vessel tracking

Min Jin Lee, Helen Hong, Jin Wook Chung

Author Affiliations +

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86691S (2013) https://doi.org/10.1117/12.2006685
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Computed tomography angiography (CTA) is currently considered noninvasive potential alternative to conventional digital subtraction angiography (DSA) for the evaluation of lower extremity arteries. For the diagnosis of peripheral arterial occlusive disease, lower extremity vessels in CTA images are extracted in advance. We propose an automatic vessel extraction method using multi-segmented volume and regional vessel tracking in lower extremity CT angiography. To consider an anatomical characteristic of each lower extremity vessel structure, whole volume is automatically divided into five segments such as foot, tibia, knee, femur and pelvis along z-axis of the lower extremities. The vessels and bones are extracted by three-dimensional region growing with multi-seeding and iterative multiple threshold estimation. Finally, to restore the eroded vessels near to bones and cavernous vessels in pelvis and tibia, regional vessel tracking considering density, size and direction is performed. Experimental results show that our method provides accurate results in occluded and stenosed vessels without loss of soft tissue and calcification. For visual scoring, two radiologists compared paired images obtained from proposed method and conventional angiography.

Citation Download Citation

Min Jin Lee, Helen Hong, and Jin Wook Chung "Automatic vessel extraction of lower extremity CT angiography using multi-segmented volume and regional vessel tracking", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86691S (13 March 2013); https://doi.org/10.1117/12.2006685

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