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In this paper, we propose a new paradigm to reconstruct 3D volume from histology slices guided by NURBS spline-based feature curves. Histology slices are first scanned into computer as a sequence of image files with a histology film scanner. An initial 3D alignment of the images is obtained through the histological similarity matching between neighboring slices. Further optimization is achieved by applying optimal affine transformation to each slice according to feature curve smoothing. Considering the intrinsic smoothness of the physical features, we compute the transformation to refine the selected features based on NURBS splines. Consequently, volume reconstruction is further optimized. We also present new evaluation methods to prove that our reconstruction scheme can achieve a high accuracy.

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In this paper, we present a novel computational modeling and simulation framework based on dynamic spherical volumetric simplex splines. The framework can handle the modeling and simulation of genus-zero objects with real physical properties. In this framework, we first develop an accurate and efficient algorithm to reconstruct the high-fidelity digital model of a real-world object with spherical volumetric simplex splines which can represent with accuracy geometric, material, and other properties of the object simultaneously. With the tight coupling of Lagrangian mechanics, the dynamic volumetric simplex splines representing the object can accurately simulate its physical behavior because it can unify the geometric and material properties in the simulation. The visualization can be directly computed from the object's geometric or physical representation based on the dynamic spherical volumetric simplex splines during simulation without interpolation or resampling. We have applied the framework for biomechanic simulation of brain deformations, such as brain shifting during the surgery and brain injury under blunt impact. We have compared our simulation results with the ground truth obtained through intra-operative magnetic resonance imaging and the real biomechanic experiments. The evaluations demonstrate the excellent performance of our new technique.

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