Locate the Superficial Femoral Artery with Occlusion by Deep Neural Network Correcting Interpolation
| Autor: | Zhong Chen, Lei Li, Chuang Xu, Wenhai Weng, Huanqin Zheng, Yijie Ku, Hui Ding, Guangzhi Wang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computed Tomography Angiography
Computer science 02 engineering and technology Thigh Occlusion 0202 electrical engineering electronic engineering information engineering medicine Computer vision Computed tomography angiography medicine.diagnostic_test Artificial neural network business.industry Superficial femoral artery Angiography food and beverages 021001 nanoscience & nanotechnology Femoral Artery medicine.anatomical_structure 020201 artificial intelligence & image processing Neural Networks Computer Artificial intelligence 0210 nano-technology business Interpolation |
| Zdroj: | EMBC |
| DOI: | 10.1109/embc44109.2020.9176650 |
| Popis: | In clinical practice, doctors usually use computed tomography angiography (CTA) to examine lower extremity atherosclerotic occlusive (ASO). Conveniently and accurately locating occlusive superficial femoral artery (SFA) which is difficult to extract from CTA can facilitate diagnosis and surgery. This paper proposed a method locating the occlusive SFA from CTA conveniently. The proposed method first takes control points at a certain interval to bicubic interpolate, and then feeds image patches generated based on the interpolation results to deep neutral network (DNN) to obtain vessel center points. The final location error is less than 9 pixels, which meets the requirements of clinical assessment accuracy. It can be used to assist the diagnosis and surgery of ASO. |
| Databáze: | OpenAIRE |
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