Clement Vachet

Adversarial regression training for visualizing the progression of chronic obstructive pulmonary disease with chest x-rays

Knowledge of what spatial elements of medical images deep learning methods use as evidence is important for model interpretability, trustiness, and validation. There is a lack of such techniques...

Interpretation of Disease Evidence for Medical Images Using Adversarial Deformation Fields

The high complexity of deep learning models is associated with the difficulty of explaining what evidence they recognize as correlating with specific disease labels. This information is critical...

Multivariate modeling of longitudinal MRI in early brain development with confidence measures

Compressive sensing based Q-space resampling for handling fast bulk motion in hardi acquisitions

A preliminary study on the effect of motion correction on HARDI reconstruction

Spatial intensity prior correction for tissue segmentation in the developing human brain

Characterizing growth patterns in longitudinal MRI using image contrast

Group-wise automatic mesh-based analysis of cortical thickness

Efficient, graph-based white matter connectivity from orientation distribution functions via multi-directional graph propagation

Software-based diffusion MR human brain phantom for evaluating fiber-tracking algorithms

UNC-Utah NA-MIC DTI framework: atlas based fiber tract analysis with application to a study of nicotine smoking addiction

Changes of MR and DTI appearance in early human brain development

Cortical Correspondence with Probabilistic Fiber Connectivity

Predicting Cognitive Outcomes by Mapping White Matter Tracts to Surface

Joint Longitudinal Modeling of Brain Appearance in Multimodal MRI for the Characterization of Early Brain Developmental Processes

Longitudinal Modeling of Multi-modal Image Contrast Reveals Patterns of Early Brain Growth