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Predictive Modeling of Anatomy with Genetic and Clinical Data
Adrian V. Dalca, Ramesh Sridharan, Mert R. Sabuncu +1
We present a semi-parametric generative model for predicting anatomy of a patient in subsequent scans following a single baseline image. Such predictive modeling promises to facili…
3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology
Henry Tregidgo, Adria Casamitjana, Caitlin Latimer +9
Neuroimaging to neuropathology correlation (NTNC) promises to enable the transfer of microscopic signatures of pathology to in vivo imaging with MRI, ultimately enhancing clinical…
Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data
Alan Q. Wang, Adrian V. Dalca, Mert R. Sabuncu
Compressed Sensing MRI (CS-MRI) has shown promise in reconstructing under-sampled MR images, offering the potential to reduce scan times. Classical techniques minimize a regularize…
Brain volume: An important determinant of functional outcome after acute ischemic stroke
Markus D. Schirmer, Kathleen L. Donahue, Marco J. Nardin +38
Objective: To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS). Methods: We analyzed cross-sectional data of the multi-site, i…
Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis
Nalini M. Singh, Juan Eugenio Iglesias, Elfar Adalsteinsson +2
We propose neural network layers that explicitly combine frequency and image feature representations and show that they can be used as a versatile building block for reconstruction…
Anatomical Predictions using Subject-Specific Medical Data
Marianne Rakic, John Guttag, Adrian V. Dalca
Changes over time in brain anatomy can provide important insight for treatment design or scientific analyses. We present a method that predicts how a brain MRI for an individual wi…