Name
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 --- 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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s10916-014-0055-8 | Journal of Medical Systems |
Keywords | Field | DocType |
coronary arteries,λ-mean operation,computed tomography angiography,region growing,discrete wavelet transformation,automatically | Computer vision,Coronary arteries,Data set,Dilation (morphology),Segmentation,Computed tomography angiography,Ground truth,Artificial intelligence,Region growing,Medicine,Wavelet | Journal |
Volume | Issue | ISSN |
38 | 6 | 1573-689X |
Citations | PageRank | References |
4 | 0.42 | 14 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuo-Tsung Chen | 1 | 58 | 12.62 |
| Pei-Kai Hung | 2 | 5 | 0.76 |
| Muh-Shi Lin | 3 | 9 | 1.19 |
| Chao-Yu Huang | 4 | 37 | 3.01 |
| Chung-Ming Chen | 5 | 176 | 16.17 |
| Tzung-Dau Wang | 6 | 4 | 1.77 |
| Wen-Jeng Lee | 7 | 14 | 2.88 |