Abstract
Abstract Computer-aided medical systems, e.g. in the fields of medical robotics or image-based assistance, are continuously investigated to overcome human limitations concerning perception, memory or dexterity. A common requirement of such systems is the availability of a digital model describing the patient’s position and morphology during a procedure. Operational complexity and technical limitations of established 3D imaging methods leave clinical settings in need of a method for the fast acquisition of a three-dimensional body surface representation. For this purpose, we propose an unsupervised and efficient body registration pipeline based on the markerless elastic registration and completion of single-view stereo range images of the body surface with statistical parametric body shape templates. Initial results show a promising representative quality of the models generated through the registration process with submillimetric fitting accuracy and realistic surface morphology, indicating the general feasibility of our approach as an instant body registration method for automated medical and biometric applications.
Highlights
The clinical success of surgical, diagnostic and therapeutic procedures exhibits a high degree of dependency upon the interactions and capabilities of medical personnel
Through the emergence of computer-aided medicine and medical automation, many conceptual solutions for negative effects caused by user-dependency and human limitations of perception, cognition, physical strength or dexterity have been developed [1]
To recover unobserved regions, promising results were achieved through the non-rigid registration of densely acquired full-body scans with template models [5] or sparse surface data with individual shape priors in form of handcrafted templates [6] or shape representations learned from subject-specific multi-view data [7]. As these approaches involve significant user-interaction and technical complexities decreasing the registration efficiency, we present a method for the unsupervised elastic registration of single-view range images with generic templates allowing the rapid and accurate digitization of the surface anatomy in clinical settings
Summary
The clinical success of surgical, diagnostic and therapeutic procedures exhibits a high degree of dependency upon the interactions and capabilities of medical personnel. Through the emergence of computer-aided medicine and medical automation, many conceptual solutions for negative effects caused by user-dependency and human limitations of perception, cognition, physical strength or dexterity have been developed [1]. Studied use cases within this research field including robotic medical ultrasound [2] indicate improvements in reliability and consistency of outcome when compared to conventional medical practice. A commonality of virtually all automated medical systems employed for physical patient in-. Body Registration Using Single-View Range Imaging and Shape Templates
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