Surface reconstruction from multiview projection data employing a microlens array-based optical detector: a simulation study

Abstract

Abstract. This article proposes a surface reconstruction method from multiview projectional data acquired by means of a rotationally mounted microlens array-based light detector (MLA-D). The technique is adapted for in vivo small animal imaging, specifically for imaging of nude mice, and does not require an additional imaging step (e.g., by means of a secondary structural modality) or additional hardware (e.g., laser-scanning approaches). Any potential point within the field of view (FOV) is evaluated by a proposed photo-consistency measure, utilizing sensor image light information as provided by elemental images (EIs). As the superposition of adjacent EIs yields depth information for any point within the FOV, the three-dimensional surface of the imaged object is estimated by a graph cuts-based method through global energy minimization. The proposed surface reconstruction is evaluated on simulated MLA-D data, incorporating a reconstructed mouse data volume as acquired by x-ray computed tomography. Compared with a previously presented back projection-based surface reconstruction method, the proposed technique yields a significantly lower error rate. Moreover, while the back projection-based method may not be able to resolve concave surfaces, this approach does. Our results further indicate that the proposed method achieves high accuracy at a low number of projections. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Musiré: multimodal simulation and reconstruction framework for the radiological imaging sciences

“…In , a single object description (phantom, atlas) can be used for the simulation of all imaging modalities. Whereas voxelized phantoms are generally employed for SPECT, PET, CT and MRI simulations, mesh-based representation of anatomical structures is preferred for the simulation of optical photons (BLI, FMI) since the imaged object’s boundary contributes crucial information on the emitted photon flux, [22,42], which constitutes a decisive factor for image reconstruction or inverse light field mapping accuracy [43].…”

Optical Three-Dimensional Surface Reconstruction and Evaluation using a Multimodality Imaging Instrumentation

“…As the visibility information of the imaged object from multiview projections is not available, methods regardless of self-occlusion are preferred, e.g., Refs. [7,8]. In addition, the light camera used herein was calibrated with a model considering the in-plane rotational angle [6], which is different from the classic calibration model used in computer vision [9].…”

“…In the Refs. [7,8], it is assumed that there is a virtual ray going through each voxel in object space and the camera's optic center. The photo-consistency measure is calculated by finding a point along the optic ray and evaluating the similarities between the formed pixel windows by the point.…”

“…dicated in Ref. [7,8], the direct average of NCC values would decrease the resolving ability of surface. Thus, a radial sampling process is performed to increase the contrast of NCC values for the calculated volume using two projection images, as shown in Fig.…”