| Content Provider |
IEEE Xplore Digital Library |
| Author |
Haak, A. Vegas-Sanchez-Ferrero, G. Mulder, H.H. Kirisli, H.A. Baka, N. Metz, C. Klein, S. Ben Ren van Burken, G. Pluim, J.P.W. van der Steen, A.F.W. van Walsum, T. Bosch, J.G. |
| Copyright Year |
2013 |
| Description |
Author affiliation: Dept. of Med. Inf. & Radiol., Erasmus MC, Rotterdam, Netherlands (Kirisli, H.A.; Baka, N.; Metz, C.; Klein, S.; van Walsum, T.) || Image Process. Lab., Valladolid Univ., Valladolid, Spain (Vegas-Sanchez-Ferrero, G.) || Imaging Sci. Inst., Univ. Med. Center, Utrecht, Netherlands (Mulder, H.H.; Pluim, J.P.W.) || Biomed. Eng., Erasmus MC, Rotterdam, Netherlands (Haak, A.; van Burken, G.; van der Steen, A.F.W.; Bosch, J.G.) || Dept. of Cardiology, Erasmus MC, Rotterdam, Netherlands (Ben Ren) |
| Abstract |
Three-dimensional transesophageal echocardiography (3D TEE) is an excellent modality for real-time visualization of the heart and monitoring of interventions. However, 3D TEE segmentation is still a challenging task due to the complex anatomy, the limited field of view, and typical ultrasound artifacts. To improve the usability of 3D TEE for monitoring interventions, we propose to segment all cavities within the TEE view with a multi-cavity Active Shape Model (ASM) derived from Computed Tomography Angiography (CTA) in conjunction with a tissue/blood classification based on a Gamma Mixture Model (GMM). 3D TEE image data of five patients were acquired with a Philips X7-2t matrix TEE probe. Tissue probability maps were estimated by a two class (blood/tissue) GMM. A statistical shape model containing left and right ventricle, left and right atrium and aorta (LV, LA, RV, LA, Ao) was derived from CTA scans of 151 patients by Principal Component Analysis. Models from individual cavities $(ASM_{part}:$ $ASM_{LV}$ etc.) and of the whole heart $(ASM_{tot})$ were generated. First, $ASM_{tot}$ was aligned with the 3D TEE by indicating 3 anatomical landmarks. Second, pose and shape of $ASM_{tot}$ were iteratively updated by a weighted update scheme excluding parts outside of the image sector. Third, shape and pose of each $ASM_{part}$ were initialized based on shape and pose of $ASM_{tot}$ and iteratively updated in a constrained manner to fit the tissue probability maps. All 3D TEE sets were manually outlined in multiple short and long axis views by two observers. The mean outline of both observers was compared to the ASM segmentations by calculating Dice coefficients. All patients had preoperative CTA scans which were segmented using an atlas approach. The TEE and the CTA segmentation were registered and Dice coefficients were computed. The Dice coefficients of the whole heart between the average observer and ASM segmentations were 0.91, 0.75, 0.87, 0.88, and 0.84 (interobserver variability: 0.95, 0.92, 0.92, 0.88, and 0.90) for TEE set 1 to 5 respectively. The Dice coefficient for the whole hart between CTA and TEE segmentation were 0.85, 0.80, 0.80, 0.81, and 0.71 and showed good agreement. In this work we could successfully show the accuracy and robustness of the proposed multi-cavity segmentation scheme. |
| Sponsorship |
IEEE Ultrason., Ferroelectr., Freq. Control Society |
| Starting Page |
659 |
| Ending Page |
662 |
| File Size |
554235 |
| Page Count |
4 |
| File Format |
PDF |
| ISSN |
19485719 |
| e-ISBN |
9781467356862 |
| DOI |
10.1109/ULTSYM.2013.0170 |
| Language |
English |
| Publisher |
Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date |
2013-07-21 |
| Publisher Place |
Czech Republic |
| Access Restriction |
Subscribed |
| Rights Holder |
Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword |
Image segmentation Shape Three-dimensional displays Observers Cavity resonators Heart Ultrasonic imaging |
| Content Type |
Text |
| Resource Type |
Article |
