ITK-based Registration of Large Images from Light Microscopy: A Biomedical Application
Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/23
New: Prefer using the following doi: https://doi.org/10.54294/abscne
Inactivation of the retinoblastoma gene in mouse embryos results in morphological changes in the placenta, which has been shown to affect fetal survivability. The construction of a 3D virtual placenta aids in accurately quantifying structural changes using image analysis. The placenta dataset consisted of 786 images totaling 550 GB in size, which were registered into a volumetric dataset using ITK's registration framework. The registration process faces many challenges arising from the large image sizes, damages during sectioning, staining gradients both within and across sections, and background noise leading to local solutions. In this work, we implement a rigorous ITK-based preprocessing pipeline for removing noise and employ a novel 2-level optimization strategy for enhanced registration in ITK. We provide 3D visualizations and numerical results to demonstrate our improvements.