naa a22 4500 510807313 CHVBK 20180411083424.0 cr unu---uuuuu 180411e20130501xx s 000 0 eng 10.1007/s11548-012-0796-0 doi (NATIONALLICENCE)springer-10.1007/s11548-012-0796-0 Compression fracture diagnosis in lumbar: a clinical CAD system [Elektronische Daten] [Samah Al-Helo, Raja Alomari, Subarna Ghosh, Vipin Chaudhary, Gurmeet Dhillon, Moh'd Al-Zoubi, Hazem Hiary, Thair Hamtini] Purpose Lower back pain affects 80-90% of all people at some point during their life time, and it is considered as the second most neurological ailment after headache. It is caused by defects in the discs, vertebrae, or the soft tissues. Radiologists perform diagnosis mainly from X-ray radiographs, MRI, or CT depending on the target organ. Vertebra fracture is usually diagnosed from X-ray radiographs or CT depending on the available technology. In this paper, we propose a fully automated Computer-Aided Diagnosis System (CAD) for the diagnosis of vertebra wedge compression fracture from CT images that integrates within the clinical routine. Methods We perform vertebrae localization and labeling, segment the vertebrae, and then diagnose each vertebra. We perform labeling and segmentation via coordinated system that consists of an Active Shape Model and a Gradient Vector Flow Active Contours (GVF-Snake). We propose a set of clinically motivated features that distinguish the fractured vertebra. We provide two machine learning solutions that utilize our features including a supervised learner (Neural Networks (NN)) and an unsupervised learner (K-Means). Results We validate our method on a set of fifty (thirty abnormal) Computed Tomography (CT) cases obtained from our collaborating radiology center. Our diagnosis detection accuracy using NN is 93.2% on average while we obtained 98% diagnosis accuracy using K-Means. Our K-Means resulted in a specificity of 87.5% and sensitivity over 99%. Conclusions We presented a fully automated CAD system that seamlessly integrates within the clinical work flow of the radiologist. Our clinically motivated features resulted in a great performance of both the supervised and unsupervised learners that we utilize to validate our CAD system. Our CAD system results are promising to serve in clinical applications after extensive validation. CARS, 2012 Vertebrae fracture nationallicence Computed Tomography (CT) nationallicence K-Means nationallicence Neural Network nationallicence Active Shape Model (ASM) nationallicence Al-Helo Samah University of Jordan, 11942, Amman, Jordan aut Alomari Raja University of Jordan, 11942, Amman, Jordan aut Ghosh Subarna University at Buffalo, SUNY, 14260, Buffalo, NY, USA aut Chaudhary Vipin University at Buffalo, SUNY, 14260, Buffalo, NY, USA aut Dhillon Gurmeet Proscan Imaging Inc., Williamsville, NY, USA aut Al-Zoubi Moh'd University of Jordan, 11942, Amman, Jordan aut Hiary Hazem University of Jordan, 11942, Amman, Jordan aut Hamtini Thair University of Jordan, 11942, Amman, Jordan aut International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/3(2013-05-01), 461-469 1861-6410 8:3<461 2013 8 11548 https://doi.org/10.1007/s11548-012-0796-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-012-0796-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Al-Helo Samah University of Jordan, 11942, Amman, Jordan aut NATIONALLICENCE 700 1- Alomari Raja University of Jordan, 11942, Amman, Jordan aut NATIONALLICENCE 700 1- Ghosh Subarna University at Buffalo, SUNY, 14260, Buffalo, NY, USA aut NATIONALLICENCE 700 1- Chaudhary Vipin University at Buffalo, SUNY, 14260, Buffalo, NY, USA aut NATIONALLICENCE 700 1- Dhillon Gurmeet Proscan Imaging Inc., Williamsville, NY, USA aut NATIONALLICENCE 700 1- Al-Zoubi Moh'd University of Jordan, 11942, Amman, Jordan aut NATIONALLICENCE 700 1- Hiary Hazem University of Jordan, 11942, Amman, Jordan aut NATIONALLICENCE 700 1- Hamtini Thair University of Jordan, 11942, Amman, Jordan aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/3(2013-05-01), 461-469 1861-6410 8:3<461 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer