Determining the spatial organization and morphological characteristics of molecularly defined cell types is a major bottleneck for characterizing the architecture underpinning brain function. We developed Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) to survey gene expression in brain tissue, as well as a turnkey computational pipeline to rapidly process large EASI-FISH image datasets. The analysis pipeline includes automated image stitching, distributed fast deformable multi-round image registration, 3D deep-learning based cell segmentation, and distributed highly accurate FISH spot detection. This pipeline can also be adapted for analysis of other image-based spatial transcriptomic datasets.