Atlas to Data Alignment with Spatially Resolved Transcriptomics Data

Oregon Convention Center 

We will address the problem of registering anatomical atlases to observed image data by simultaneously estimating a non-linear spatial transformation of the atlas and a probabilistic correspondence between the atlas labels and the observed image values. This approach can be applied to spatially resolved transcriptomics data, where the image modality can be transformed into probability distributions over cell types in each segmented region. The non-linear spatial transformation uses the large deformation diffeomorphic mapping algorithm. We will describe the relevant algorithm and provide experimental results.