Multi-Atlas Image Soft Segmentation via Computation of the Expected Label Value
| العنوان: | Multi-Atlas Image Soft Segmentation via Computation of the Expected Label Value |
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| المؤلفون: | Iman Aganj, Bruce Fischl |
| المصدر: | IEEE transactions on medical imaging |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | supervised image segmentation, Computer science, Computation, Article, 030218 nuclear medicine & medical imaging, Convolution, Expected label value (ELV), 03 medical and health sciences, 0302 clinical medicine, Image Processing, Computer-Assisted, medicine, Medical imaging, atlas, Computer vision, Segmentation, Electrical and Electronic Engineering, Probability, Radiological and Ultrasound Technology, medicine.diagnostic_test, Atlas (topology), business.industry, Brain, Magnetic resonance imaging, Image segmentation, soft segmentation, Magnetic Resonance Imaging, Computer Science Applications, Transformation (function), Artificial intelligence, Tomography, X-Ray Computed, business, Algorithms, Software, MRI, CT |
| الوصف: | The use of multiple atlases is common in medical image segmentation. This typically requires deformable registration of the atlases (or the average atlas) to the new image, which is computationally expensive and susceptible to entrapment in local optima. We propose to instead consider the probability of all possible atlas-to-image transformations and compute the expected label value (ELV) , thereby not relying merely on the transformation deemed “optimal” by the registration method. Moreover, we do so without actually performing deformable registration, thus avoiding the associated computational costs. We evaluate our ELV computation approach by applying it to brain, liver, and pancreas segmentation on datasets of magnetic resonance and computed tomography images. |
| تدمد: | 1558-254X 0278-0062 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57cbf3fd00116f6f308e315b87a9ac59 https://doi.org/10.1109/tmi.2021.3064661 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....57cbf3fd00116f6f308e315b87a9ac59 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 1558254X 02780062 |
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