Abstract
Quantitative in vitro receptor auto-radiographic studies in brains require the preparation of thin microtome sections. Due to the sectioning process, the spatial coherence is lost and needs to be recovered, if 3D analysis is envisaged. This study describes a new processing pipeline for 3D realignment of auto-radiographs of rat brain sections based on image features. Automatically extracted image features from neighboring sections are matched using their descriptors by rejecting false matches. An intermediate objective is to achieve an intra-subject reconstruction to reduce the manual effort in the next registration step. These steps are followed by a semi-automatic method which aligns already preregistered auto-radiographic stacks into a blockface reference volume to ensure anatomical correctness. The validity of the approach is illustrated by using the mean squared error between the user-defined landmarks as the quality measure.
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Huynh, AM. et al. (2015). Reconstructing a Series of Auto-Radiographic Images in Rat Brains. In: Handels, H., Deserno, T., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2015. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46224-9_30
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DOI: https://doi.org/10.1007/978-3-662-46224-9_30
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