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.