416 citations · 748 across the 56 of their papers we have counts for
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Self-supervised Landmark Learning with Deformation Reconstruction and Cross-subject Consistency Objectives
Chun-Hung Chao, Marc Niethammer
A Point Distribution Model (PDM) is the basis of a Statistical Shape Model (SSM) that relies on a set of landmark points to represent a shape and characterize the shape variation.…
Multimodal Understanding Through Correlation Maximization and Minimization
Yifeng Shi, Marc Niethammer
Multimodal learning has mainly focused on learning large models on, and fusing feature representations from, different modalities for better performances on downstream tasks. In th…
Inverse Consistency by Construction for Multistep Deep Registration
Hastings Greer, Lin Tian, Francois-Xavier Vialard +5
Inverse consistency is a desirable property for image registration. We propose a simple technique to make a neural registration network inverse consistent by construction, as a con…
Unsupervised Discovery of 3D Hierarchical Structure with Generative Diffusion Features
Nurislam Tursynbek, Marc Niethammer
Inspired by recent findings that generative diffusion models learn semantically meaningful representations, we use them to discover the intrinsic hierarchical structure in biomedic…
MRIS: A Multi-modal Retrieval Approach for Image Synthesis on Diverse Modalities
Boqi Chen, Marc Niethammer
Multiple imaging modalities are often used for disease diagnosis, prediction, or population-based analyses. However, not all modalities might be available due to cost, different st…
NAISR: A 3D Neural Additive Model for Interpretable Shape Representation
Yining Jiao, Carlton Zdanski, Julia Kimbell +8
Deep implicit functions (DIFs) have emerged as a powerful paradigm for many computer vision tasks such as 3D shape reconstruction, generation, registration, completion, editing, an…
Exploring Cycle Consistency Learning in Interactive Volume Segmentation
Qin Liu, Meng Zheng, Benjamin Planche +4
Automatic medical volume segmentation often lacks clinical accuracy, necessitating further refinement. In this work, we interactively approach medical volume segmentation via two d…