Cardiac Multi-detector CT Segmentation Based on Multiscale Directional Edge Detector and 3D Level Set
| Autor: | Sofia Antunes 1, 2, Antonio Esposito 1, 3, Anna Palmisano 1, 3 Caterina Colantoni 1, Sergio Cerutti 2, Giovanna Rizzo 4 |
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| Přispěvatelé: | Antunes, S, Esposito, Antonio, Palmisano, A, Colantoni, C, Cerutti, S, Rizzo, G. |
| Rok vydání: | 2015 |
| Předmět: |
Adult
Male Mean squared error Computer science Heart Ventricles Biomedical Engineering Boundary (topology) Scale-space segmentation 02 engineering and technology Edge detection Filter bank 030218 nuclear medicine & medical imaging 03 medical and health sciences symbols.namesake Imaging Three-Dimensional 0302 clinical medicine Level set Multidetector Computed Tomography 0202 electrical engineering electronic engineering information engineering Humans Computer vision Segmentation cardiovascular diseases Aged business.industry Middle Aged Gaussian filter cardiovascular system symbols Female 020201 artificial intelligence & image processing Artificial intelligence Cardiac segmentation Cardiomyopathies business Pericardium Endocardium Biomedical engineering |
| Zdroj: | Annals of biomedical engineering (Online) 44 (2016): 1487–1501. doi:10.1007/s10439-015-1422-4 info:cnr-pdr/source/autori:Sofia Antunes 1,2, Antonio Esposito 1,3, Anna Palmisano 1,3 Caterina Colantoni 1,3, Sergio Cerutti 2, Giovanna Rizzo 4/titolo:Cardiac Multi-detector CT Segmentation Based on Multiscale Directional Edge Detector and 3D Level Set./doi:10.1007%2Fs10439-015-1422-4/rivista:Annals of biomedical engineering (Online)/anno:2016/pagina_da:1487/pagina_a:1501/intervallo_pagine:1487–1501/volume:44 |
| ISSN: | 1573-9686 0090-6964 |
| DOI: | 10.1007/s10439-015-1422-4 |
| Popis: | Extraction of the cardiac surfaces of interest from multi-detector computed tomographic (MDCT) data is a pre-requisite step for cardiac analysis, as well as for image guidance procedures. Most of the existing methods need manual corrections, which is time-consuming. We present a fully automatic segmentation technique for the extraction of the right ventricle, left ventricular endocardium and epicardium from MDCT images. The method consists in a 3D level set surface evolution approach coupled to a new stopping function based on a multiscale directional second derivative Gaussian filter, which is able to stop propagation precisely on the real boundary of the structures of interest. We validated the segmentation method on 18 MDCT volumes from healthy and pathologic subjects using manual segmentation performed by a team of expert radiologists as gold standard. Segmentation errors were assessed for each structure resulting in a surface-to-surface mean error below 0.5 mm and a percentage of surface distance with errors less than 1 mm above 80%. Moreover, in comparison to other segmentation approaches, already proposed in previous work, our method presented an improved accuracy (with surface distance errors less than 1 mm increased of 8-20% for all structures). The obtained results suggest that our approach is accurate and effective for the segmentation of ventricular cavities and myocardium from MDCT images. |
| Databáze: | OpenAIRE |
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