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Chapter and Conference Paper
Feature Selection for Malapposition Detection in Intravascular Ultrasound - A Comparative Study
Coronary atherosclerosis is a leading cause of morbidity and mortality worldwide. It is often treated by placing stents in the coronary arteries. Inappropriately placed stents or malappositions can result in p...
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Chapter and Conference Paper
Boundary-Weighted Logit Consistency Improves Calibration of Segmentation Networks
Neural network prediction probabilities and accuracy are often only weakly-correlated. Inherent label ambiguity in training data for image segmentation aggravates such miscalibration. We show that logit consis...
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Chapter and Conference Paper
Learning Probabilistic Piecewise Rigid Atlases of Model Organisms via Generative Deep Networks
Atlases are crucial to imaging statistics as they enable the standardization of inter-subject and inter-population analyses. While existing atlas estimation methods based on fluid/elastic/diffusion registratio...
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Chapter and Conference Paper
ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration
Establishing voxelwise semantic correspondence across distinct imaging modalities is a foundational yet formidable computer vision task. Current multi-modality registration techniques maximize hand-crafted int...
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Chapter and Conference Paper
Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI
Current deep learning approaches for diffusion MRI modeling circumvent the need for densely-sampled diffusion-weighted images (DWIs) by directly predicting microstructural indices from sparsely-sampled DWIs. H...
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Chapter and Conference Paper
Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data
We present a rotation-equivariant self-supervised learning framework for the sparse deconvolution of non-negative scalar fields on the unit sphere. Spherical signals with multiple peaks naturally arise in Dif...
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Chapter and Conference Paper
Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography
Optical Coherence Tomography (OCT) is pervasive in both the research and clinical practice of Ophthalmology. However, OCT images are strongly corrupted by noise, limiting their interpretation. Current OCT deno...
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Chapter and Conference Paper
Robust Non-negative Tensor Factorization, Diffeomorphic Motion Correction, and Functional Statistics to Understand Fixation in Fluorescence Microscopy
Fixation is essential for preserving cellular morphology in biomedical research. However, it may also affect spectra captured in multispectral fluorescence microscopy, impacting molecular interpretations. To i...
