تقرير
Pulmonary Vascular Tree Segmentation from Contrast-Enhanced CT Images
| العنوان: | Pulmonary Vascular Tree Segmentation from Contrast-Enhanced CT Images |
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| المؤلفون: | Helmberger, M., Urschler, M., Pienn, M., Balint, Z., Olschewski, A., Bischof, H. |
| سنة النشر: | 2013 |
| المجموعة: | Computer Science Physics (Other) |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Physics - Medical Physics |
| الوصف: | We present a pulmonary vessel segmentation algorithm, which is fast, fully automatic and robust. It uses a coarse segmentation of the airway tree and a left and right lung labeled volume to restrict a vessel enhancement filter, based on an offset medialness function, to the lungs. We show the application of our algorithm on contrast-enhanced CT images, where we derive a clinical parameter to detect pulmonary hypertension (PH) in patients. Results on a dataset of 24 patients show that quantitative indices derived from the segmentation are applicable to distinguish patients with and without PH. Further work-in-progress results are shown on the VESSEL12 challenge dataset, which is composed of non-contrast-enhanced scans, where we range in the midfield of participating contestants. Comment: Part of the OAGM/AAPR 2013 proceedings (1304.1876) |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1304.7140 |
| رقم الأكسشن: | edsarx.1304.7140 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |