Nerve Detection in Ultrasound Images Using Median Gabor Binary Pattern
| العنوان: | Nerve Detection in Ultrasound Images Using Median Gabor Binary Pattern |
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| المؤلفون: | Adel Hafiane, Donatello Conte, Pascal Makris, Pierre Vieyres, Oussama Hadjerci, Alain Delbos |
| المساهمون: | Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique (PRISME), Université d'Orléans (UO)-Ecole Nationale Supérieure d'Ingénieurs de Bourges (ENSI Bourges), Laboratoire d'Informatique Fondamentale et Appliquée de Tours (LIFAT), Centre National de la Recherche Scientifique (CNRS)-Université de Tours-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Clinique Medipole Garonne, Université de Tours (UT)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS) |
| المصدر: | Lecture Notes in Computer Science ISBN: 9783319117546 ICIAR (2) 11th International Conference, ICIAR 2014 11th International Conference, ICIAR 2014, Oct 2014, Villamoura, Portugal. pp.132-140, ⟨10.1007/978-3-319-11755-3_15⟩ |
| بيانات النشر: | Springer International Publishing, 2014. |
| سنة النشر: | 2014 |
| مصطلحات موضوعية: | genetic structures, Computer science, nerve detection, Feature extraction, 02 engineering and technology, supervised learning, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Gabor filter, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, image texture analysis, 0202 electrical engineering, electronic engineering, information engineering, Computer vision, Segmentation, image segmentation, business.industry, feature extraction, Ultrasound, Supervised learning, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, Image segmentation, Binary pattern, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], 020201 artificial intelligence & image processing, Noise (video), Artificial intelligence, business |
| الوصف: | International audience; Ultrasound in regional anesthesia (RA) has increased in pop-ularity over the last years. The nerve localization presents a key step for RA practice, it is therefore valuable to develop a tool able to facilitate this practice. The nerve detection in the ultrasound images is a challeng-ing task, since the noise and other artifacts corrupt the visual properties of such kind of tissue. In this paper we propose a new method to address this problem. The proposed technique operates in two steps. As the me-dian nerve belongs to a hyperechoic region, the first step consists in the segmentation of this type of region using the k-means algorithm. The second step is more critical; it deals with nerve structure detection in noisy data. For that purpose, a new descriptor is developed. It combines tow methods median binary pattern (MBP) and Gabor filter to obtain the median Gabor binary pattern (MGBP). The method was tested on 173 ultrasound images of the median nerve obtained from three patients. The results showed that the proposed approach achieves better accuracy than the original MBP, Gabor descriptor and other popular descriptors. |
| ردمك: | 978-3-319-11754-6 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96b1be049d2c84ee2721a1b75a64d401Test https://doi.org/10.1007/978-3-319-11755-3_15Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....96b1be049d2c84ee2721a1b75a64d401 |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783319117546 |
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