Liver Segmentation in Abdominal CT Images Using Probabilistic Atlas and Adaptive 3D Region Growing
| Autor: | Kayvan Najarian, Shima Rafiei, Banafsheh Felfeliyan, Shadrokh Samavi, Behzad Mirmahboub, S. M. Reza Soroushmehr, Nader Karimi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Abdominal ct 02 engineering and technology computer.software_genre Liver segmentation 030218 nuclear medicine & medical imaging 03 medical and health sciences Imaging Three-Dimensional 0302 clinical medicine Voxel Abdomen Image Processing Computer-Assisted 0202 electrical engineering electronic engineering information engineering Humans Diagnosis Computer-Assisted Probabilistic atlas Atlas (topology) business.industry Pattern recognition Image segmentation Liver Region growing 020201 artificial intelligence & image processing Artificial intelligence Tomography X-Ray Computed business computer Algorithms |
| Zdroj: | EMBC |
| DOI: | 10.1109/embc.2019.8857835 |
| Popis: | Automatic liver segmentation plays a vital role in computer-aided diagnosis or treatment. Manual segmentation of organs is a tedious and challenging task and is prone to human errors. In this paper, we propose innovative pre-processing and adaptive 3D region growing methods with subject-specific conditions. To obtain strong edges and high contrast, we propose effective contrast enhancement algorithm then we use the atlas intensity distribution of most probable voxels in probability maps along with location before designing conditions for our 3D region growing method. We also incorporate the organ boundary to restrict the region growing. We compare our method with the label fusion of 13 organs on state-of-the-art Deeds registration method and achieved Dice score of 92.56%. |
| Databáze: | OpenAIRE |
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