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We present an automatic method for assessment of pectus excavatum severity based on an optical 3-D markerless shape measurement. A four-directional measurement system based on a structured light projection method is built to capture the shape of the body surface of the patients. The system setup is described and typical measurement parameters are given. The automated data analysis path is explained. Their main steps are: normalization of trunk model orientation, cutting the model into slices, analysis of each slice shape, selecting the proper slice for the assessment of pectus excavatum of the patient, and calculating its shape parameter. We develop a new shape parameter (I(3ds)) that shows high correlation with the computed tomography (CT) Haller index widely used for assessment of pectus excavatum. Clinical results and the evaluation of developed indexes are presented.

Abstract. Faulty postures, scoliosis and sagittal plane deformities should be detected as early as possible to apply preventive and treatment measures against major clinical consequences. To support documentation of the severity of deformity and diminish x-ray exposures, several solutions utilizing analysis of back surface topography data were introduced. A novel approach to automatic recognition and localization of anatomical landmarks of the human back is presented that may provide more repeatable results and speed up the whole procedure. The algorithm was designed as a two-step process involving a statistical model built upon expert knowledge and analysis of threedimensional back surface shape data. Voronoi diagram is used to connect mean geometric relations, which provide a first approximation of the positions, with surface curvature distribution, which further guides the recognition process and gives final locations of landmarks. Positions obtained using the developed algorithms are validated with respect to accuracy of manual landmark indication by experts. Preliminary validation proved that the landmarks were localized correctly, with accuracy depending mostly on the characteristics of a given structure. It was concluded that recognition should mainly take into account the shape of the back surface, putting as little emphasis on the statistical approximation as possible.

The existing methods for measuring the shape of the human body in motion are limited in their practical application owing to immaturity, complexity, and/or high price. Therefore, we propose a method based on structured light supported by multispectral separation to achieve multidirectional and parallel acquisition. Single-frame fringe projection is employed in this method for detailed geometry reconstruction. An extended phase unwrapping method adapted for measurement of the human body is also proposed. This method utilizes local fringe parameter information to identify the optimal unwrapping path for reconstruction. Subsequently, we present a prototype 4DBODY system with a working volume of 2.0 × 1.5 × 1.5 m3, a measurement uncertainty less than 0.5 mm and an average spatial resolution of 1.0 mm for three-dimensional (3D) points. The system consists of eight directional 3D scanners functioning synchronously with an acquisition frequency of 120 Hz. The efficacy of the proposed system is demonstrated by presenting the measurement results obtained for known geometrical objects moving at various speeds as well actual human movements.

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