Abstract: Computed Tomography (CT) images are a crucial resource for assessing the severity and prognosis of bone injuries caused by trauma or accident. Fracture detection in long bones is a very challenging task due to the limited resolution of the original CT images, the complexity of bone structures, and their possible fractures. Also, CT images are also susceptible to noise, partial volume effects, and intensity inhomogeneities. These make fracture detection more challenging and laborious. Sometimes accurate fractured part segmentation and labeling require the participation of experts. Due to these aspects of the orthopedic field focusing on developing automated computer-aided diagnosis (CAD) systems for bone fracture detection and analysis. We have developed a CAD system that not only precisely extracts and assigns the unique labels to each fractured piece by considering patient-specific bone anatomy but also effectively removes the unwanted artifacts (like flesh) surrounded by bone tissues. In addition to this, the system will provide several fracture features such as a number of bones and number of fractures pieces per bone to analyze the severity moreover to decide a more optimal recovery plan/process. In the proposed system, experiments are conducted on real patient-specific CT images and have shown 95% accuracy. Along with comparing the results with several states of the art segmentation methods, the results of the proposed system is compared with the clinical ground truth (i.e., annotated CT images) collected from experts. By confirming results of the proposed method effective solution for bone fractures detection and analysis.

Biography: Dr. R. S. Hegadi has completed MCA in 1995, MPhil in 2003 and PhD in 2007 from Gulbarga University, Kalaburagi. He worked as Lecturer in Government College, Raichur from Feb-1997 to Jan-2008, in Government First Grade College, Vijayanagar, Bangalore from Jan-2008 to July-2008 and as Assistant Professor at Karnatak University, Dharwad from July-2008 to January-2012. He joined Solapur University as Associate Professor in February-2012 and worked as Professor and Head of the Department of Computer Science at Solapur University, Solapur from 2015 to January 2020. He also held additional charges of Director, School of Computer Science, Director, IQAC and Coordinator, Instrumentation Centre, Solapur University, Solapur. From 2021 onwards he is working as Dean, School of Computer Science at Central University of Karnataka, Dean Students Welfare (DSW) and Nodal Officer – Project Samarth, Ministry of Education, Government of India. He has published more than 150 research articles in reputed international journals and conference proceedings. He authored six books and thirty book chapters. He has guided 15 MPhil students and 13 PhD scholars and currently 2 PhD scholars are working for PhD under his guidance. His domain of research is medical simulator development, biometric, document image analysis, computer vision, robotics, etc. with research contribution using deap neural networks, convolutional neural networks, graph networks, deformable models, etc. He has completed one UGC major research project worth Rs. 9.71 Lacs and currently he has two research projects from the Department of Electronics and IT, New Delhi each worth Rs. 50.06 Lacs and three project fellows are working in these projects. He visited Hong King in 2006, Sydney, Australia in 2010, Florida, USA in 2012 and Dhaka in 2015 for presenting his paper at international conferences. He has delivered more than 30 keynote speeches/invited talks in national and international conferences/symposia. He organized many workshops and conferences.