Development and evaluation of statistical shape modeling for principal inner organs on torso CT images
| Autor: | Shoji Kido, Xiangrong Zhou, Ryujiro Yokoyama, Hiroaki Hoshi, Hiroshi Fujita, Rui Xu, Masayuki Kanematsu, Takeshi Hara, Yasushi Hirano |
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| Rok vydání: | 2014 |
| Předmět: |
Radiation
business.industry Torso Physical Therapy Sports Therapy and Rehabilitation General Medicine Statistical shape modeling Imaging Three-Dimensional Tomography x ray computed medicine.anatomical_structure Compact space Point distribution model Organ Specificity Active shape model medicine Humans Computer Simulation Radiology Nuclear Medicine and imaging Computer vision Artificial intelligence Tomography X-Ray Computed business Minimum description length Mathematics Shape analysis (digital geometry) |
| Zdroj: | Radiological Physics and Technology. 7:277-283 |
| ISSN: | 1865-0341 1865-0333 |
| DOI: | 10.1007/s12194-014-0261-6 |
| Popis: | The shapes of the inner organs are important information for medical image analysis. Statistical shape modeling provides a way of quantifying and measuring shape variations of the inner organs in different patients. In this study, we developed a universal scheme that can be used for building the statistical shape models for different inner organs efficiently. This scheme combines the traditional point distribution modeling with a group-wise optimization method based on a measure called minimum description length to provide a practical means for 3D organ shape modeling. In experiments, the proposed scheme was applied to the building of five statistical shape models for hearts, livers, spleens, and right and left kidneys by use of 50 cases of 3D torso CT images. The performance of these models was evaluated by three measures: model compactness, model generalization, and model specificity. The experimental results showed that the constructed shape models have good "compactness" and satisfied the "generalization" performance for different organ shape representations; however, the "specificity" of these models should be improved in the future. |
| Databáze: | OpenAIRE |
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