1 citations · 1 across the 6 of their papers we have counts for
6 papers
Improving Neuropathological Reconstruction Fidelity via AI Slice Imputation
Marina Crespo Aguirre, Jonathan Williams-Ramirez, Dina Zemlyanker +13
Neuropathological analyses benefit from spatially precise volumetric reconstructions that enhance anatomical delineation and improve morphometric accuracy. Our prior work has shown…
Deep generative priors for 3D brain analysis
Ana Lawry Aguila, Dina Zemlyanker, You Cheng +6
Diffusion models have recently emerged as powerful generative models in medical imaging. However, it remains a major challenge to combine these data-driven models with domain knowl…
Automated Segmentation of Coronal Brain Tissue Slabs for 3D Neuropathology
Jonathan Williams Ramirez, Dina Zemlyanker, Lucas Deden-Binder +15
Advances in image registration and machine learning have recently enabled volumetric analysis of postmortem brain tissue from conventional photographs of coronal slabs, which are r…
From Low Field to High Value: Robust Cortical Mapping from Low-Field MRI
Karthik Gopinath, Annabel Sorby-Adams, Jonathan W. Ramirez +12
Three-dimensional reconstruction of cortical surfaces from MRI for morphometric analysis is fundamental for understanding brain structure. While high-field MRI (HF-MRI) is standard…
Learning to Upscale 3D Segmentations in Neuroimaging
Xiaoling Hu, Peirong Liu, Dina Zemlyanker +3
Obtaining high-resolution (HR) segmentations from coarse annotations is a pervasive challenge in computer vision. Applications include inferring pixel-level segmentations from toke…
Reference-Free 3D Reconstruction of Brain Dissection Slabs via Learned Atlas Coordinates
Lin Tian, Jonathan Williams-Ramirez, Dina Zemlyanker +14
Correlation of neuropathology with MRI has the potential to transfer microscopic signatures of pathology to in vivo scans. There is increasing interest in building these correlatio…