73 citations · 305 across the 55 of their papers we have counts for
8 papers · 1 filter
Patient-specific Conditional Joint Models of Shape, Image Features and Clinical Indicators
Bernhard Egger, Markus D. Schirmer, Florian Dubost +3
We propose and demonstrate a joint model of anatomical shapes, image features and clinical indicators for statistical shape modeling and medical image analysis. The key idea is to…
Fetal Pose Estimation in Volumetric MRI using a 3D Convolution Neural Network
Junshen Xu, Molin Zhang, Esra Abaci Turk +5
The performance and diagnostic utility of magnetic resonance imaging (MRI) in pregnancy is fundamentally constrained by fetal motion. Motion of the fetus, which is unpredictable an…
BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes
Razvan V. Marinescu, Arman Eshaghi, Daniel C. Alexander +1
We present BrainPainter, a software that automatically generates images of highlighted brain structures given a list of numbers corresponding to the output colours of each region.…
Unsupervised Deep Learning for Bayesian Brain MRI Segmentation
Adrian V. Dalca, Evan Yu, Polina Golland +3
Probabilistic atlas priors have been commonly used to derive adaptive and robust brain MRI segmentation algorithms. Widely-used neuroimage analysis pipelines rely heavily on these…
Joint inference on structural and diffusion MRI for sequence-adaptive Bayesian segmentation of thalamic nuclei with probabilistic atlases
Juan Eugenio Iglesias, Koen Van Leemput, Polina Golland +1
Segmentation of structural and diffusion MRI (sMRI/dMRI) is usually performed independently in neuroimaging pipelines. However, some brain structures (e.g., globus pallidus, thalam…
Temporal Registration in Application to In-utero MRI Time Series
Ruizhi Liao, Esra A. Turk, Miaomiao Zhang +4
We present a robust method to correct for motion in volumetric in-utero MRI time series. Time-course analysis for in-utero volumetric MRI time series often suffers from substantial…
Placental Flattening via Volumetric Parameterization
S. Mazdak Abulnaga, Esra Abaci Turk, Mikhail Bessmeltsev +3
We present a volumetric mesh-based algorithm for flattening the placenta to a canonical template to enable effective visualization of local anatomy and function. Monitoring placent…
Semi-supervised Learning for Quantification of Pulmonary Edema in Chest X-Ray Images
Ruizhi Liao, Jonathan Rubin, Grace Lam +5
We propose and demonstrate machine learning algorithms to assess the severity of pulmonary edema in chest x-ray images of congestive heart failure patients. Accurate assessment of…