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High energy impacts at joint locations often generate highly fragmented, or comminuted, bone fractures. A leading current approach for treatment requires physicians qualitatively to classify the fracture to one of four possible fracture severity cases. It has been observed that qualitative evaluation of fracture severity by physicians can vary significantly which can lead to potential misclassification and mistreatment of these fracture cases. The system described in this book applies novel three-dimensional (3D) puzzle-solving algorithms to identify the fracture fragments in the CT image data and piece them back together in a virtual environment. Doing so provides quantitative values for both fracture surface area and dispersion that reduce variability in fracture severity classifications and prevent mis-diagnosis for fracture cases that may be difficult to qualitatively classify using traditional approaches. This book describes the system, the underlying algorithms and demonstrates the virtual reconstruction results and quantitative analysis of comminuted bone fractures from six clinical cases.

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Pengcheng Liu received his PhD from the University of North Carolina at Charlotte in 2012. His focus was on digital signal processing, 2D and 3D image analysis, pattern recognition and data mining. He is the one of few people who researched, designed and developed the Omneo Cloud application

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