Name
Title | ||
|---|---|---|
Well-balanced system for coronary calcium detection and volume measurement in a low resolution intravascular ultrasound videos. |
Abstract | ||
|---|---|---|
BackgroundAccurate and fast quantitative assessment of calcium volume is required during the planning of percutaneous coronary interventions procedures. Low resolution in intravascular ultrasound (IVUS) coronary videos poses a threat to calcium detection causing over-estimation in volume measurement. We introduce a correction block that counter-balances the bias introduced during the calcium detection process. MethodNineteen patients image dataset (around 40,090 frames), IRB approved, were collected using 40MHz IVUS catheter (Atlantis SR Pro, Boston Scientific, pullback speed of 0.5mm/sec). A new set of 20 generalized and well-balanced systems each consisting of three stages: (i) calcium detection, (ii) calibration and (iii) measurement, while ensuring accuracy of four soft classifiers (Threshold, FCM, K-means and HMRF) and workflow speed using five multiresolution techniques (bilinear, bicubic, wavelet, Lanczos, Gaussian Pyramid) were designed. Results of the three calcium detection methods were benchmarked against the Threshold-based method. ResultsAll 20 well-balanced systems with calibration block show superior performance. Using calibration block, FCM versus Threshold-based method shows the highest cross-correlation 0.99 (P |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.compbiomed.2017.03.026 | Comp. in Bio. and Med. |
Keywords | Field | DocType |
Calibration,Classification,Coronary calcium volume,Low-resolution IVUS,Multiresolution,Speed | Computer vision,Lanczos resampling,Pattern recognition,Intravascular ultrasound,Computer science,Bicubic interpolation,Artificial intelligence,Jaccard index,Calibration,Bilinear interpolation,Performance improvement,Wavelet | Journal |
Volume | Issue | ISSN |
84 | C | 0010-4825 |
Citations | PageRank | References |
3 | 0.40 | 10 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sumit K. Banchhor | 1 | 28 | 4.19 |
| Narendra D. Londhe | 2 | 98 | 13.85 |
| Tadashi Araki | 3 | 45 | 7.72 |
| Luca Saba | 4 | 202 | 24.44 |
| Petia Radeva | 5 | 7 | 1.14 |
| John R. Laird | 6 | 21 | 4.23 |
| Jasjit S. Suri | 7 | 1754 | 128.89 |
| Fellow AIMBE | 8 | 3 | 0.40 |