title: DWT-based segmentation method for coronary arteries.
abstract: This work presents a new method for segmenting coronary arteries automatically in computed tomography angiography (CTA) data sets. The method automatically isolates heart and coronary arteries from surrounding structures and search for the probable location of coronary arteries by 3D region growing. Based on the dilation of the probable location, discrete wavelet transformation (DWT) and λ - mean operation complete accurate detection of coronary arties. Finally, the proposed method is tested on clinical CTA data-sets. The results on clinical datasets show that the proposed method is able to extract each branch of arteries when comparing to commercial software GE Healthcare and delineated ground truth.
authors.affiliation: Institute of Biomedical Engineering, National Taiwan University, Taipei, 10617, Taiwan, Republic of China, shough34@yahoo.com.tw.
authors.forename: Shuo-Tsung
authors.initials: ST
authors.lastname: Chen
authors.forename: Pei-Kai
authors.initials: PK
authors.lastname: Hung
authors.forename: Muh-Shi
authors.initials: MS
authors.lastname: Lin
authors.forename: Chao-Yu
authors.initials: CY
authors.lastname: Huang
authors.forename: Chung-Ming
authors.initials: CM
authors.lastname: Chen
authors.forename: Tzung-Dau
authors.initials: TD
authors.lastname: Wang
authors.forename: Wen-Jeng
authors.initials: WJ
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D017023:Coronary Angiography / Q000379:methods*; D006801:Humans; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods*; D058067:Wavelet Analysis