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| Author | Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | A Holistic Approach for the Detection of Media-Adventitia Border in IVUS | Type | Conference Article | ||
| Year | 2011 | Publication | 14th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
| Volume | 6893 | Issue | Pages | 401-408 | |
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| Abstract | In this paper we present a methodology for the automatic detection of media-adventitia border (MAb) in Intravascular Ultrasound. A robust computation of the MAb is achieved through a holistic approach where the position of the MAb with respect to other tissues of the vessel is used. A learned quality measure assures that the resulting MAb is optimal with respect to all other tissues. The mean distance error computed through a set of 140 images is 0.2164 (±0.1326) mm. | ||||
| Address | Toronto, Canada | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-23625-9 | Medium | |
| Area | Expedition | Conference | MICCAI | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPG2011 | Serial | 1739 | ||
| Permanent link to this record | |||||
| Author | Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin Yuste; Petia Radeva | ||||
| Title | Accurate and Robust Fully-Automatic QCA: Method and Numerical Validation | Type | Conference Article | ||
| Year | 2011 | Publication | 14th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
| Volume | 14 | Issue | 3 | Pages | 496-503 |
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| Abstract | The Quantitative Coronary Angiography (QCA) is a methodology used to evaluate the arterial diseases and, in particular, the degree of stenosis. In this paper we propose AQCA, a fully automatic method for vessel segmentation based on graph cut theory. Vesselness, geodesic paths and a new multi-scale edgeness map are used to compute a globally optimal artery segmentation. We evaluate the method performance in a rigorous numerical way on two datasets. The method can detect an artery with precision 92.9 +/- 5% and sensitivity 94.2 +/- 6%. The average absolute distance error between detected and ground truth centerline is 1.13 +/- 0.11 pixels (about 0.27 +/- 0.025 mm) and the absolute relative error in the vessel caliber estimation is 2.93% with almost no bias. Moreover, the method can discriminate between arteries and catheter with an accuracy of 96.4%. | ||||
| Address | Toronto, Canada | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-23625-9 | Medium | ||
| Area | Expedition | Conference | MICCAI | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ HGE2011 | Serial | 1769 | ||
| Permanent link to this record | |||||