Atlas-based organ & bone approximation for ex-vivo μMRI mouse data: A pilot study
In this paper we propose a novel semi-automated atlas-based approach for organ and bone approximation for micro-Magnetic Resonance Imaging (μMRI) data of mice. Based on a set of 18 manually indicated landmarks at specific joint & bone locations, individual atlas bones (pelvis, limb bones and sternum) are mapped to the target in a first step and a sparse set of corresponding landmarks on a skin surface representation is determined in a second step. Subsequently, this sparse set on the skin is used to derive a dense set of correspondences relying on matching spectra of local geodesic distances. Finally, determined by the skin correspondence, a Thin-Plate-Spline (TPS) approximation of major organs (heart, lungs, liver, spleen, stomach, kidneys) is performed. The method was tested using 3 µMRI mouse datasets and the MOBY atlas. The performance of the organ approximation algorithm was estimated using manual segmentations of 6 organs for each MRI dataset and calculating Dice indices of organ-volume overlap for each dataset and the atlas. The obtained results indicate excellent fitting of heart and kidneys and moderate fitting of spleen, lungs, liver and stomach. These initial results are satisfactory and comparable to other organ mapping studies using different approaches and μComputed Tomography (CT) mouse data.