53 citations · 66 across the 7 of their papers we have counts for
7 papers
Shape-aware Segmentation of the Placenta in BOLD Fetal MRI Time Series
S. Mazdak Abulnaga, Neel Dey, Sean I. Young +6
Blood oxygen level dependent (BOLD) MRI time series with maternal hyperoxia can assess placental oxygenation and function. Measuring precise BOLD changes in the placenta requires a…
Dynamic Neural Fields for Learning Atlases of 4D Fetal MRI Time-series
Zeen Chi, Zhongxiao Cong, Clinton J. Wang +6
We present a method for fast biomedical image atlas construction using neural fields. Atlases are key to biomedical image analysis tasks, yet conventional and deep network estimati…
Geometry Aware Field-to-field Transformations for 3D Semantic Segmentation
Dominik Hollidt, Clinton Wang, Polina Golland +1
We present a novel approach to perform 3D semantic segmentation solely from 2D supervision by leveraging Neural Radiance Fields (NeRFs). By extracting features along a surface poin…
Interpolating between Images with Diffusion Models
Clinton J. Wang, Polina Golland
One little-explored frontier of image generation and editing is the task of interpolating between two input images, a feature missing from all currently deployed image generation p…
Automatic Segmentation of the Placenta in BOLD MRI Time Series
S. Mazdak Abulnaga, Sean I. Young, Katherine Hobgood +5
Blood oxygen level dependent (BOLD) MRI with maternal hyperoxia can assess oxygen transport within the placenta and has emerged as a promising tool to study placental function. Mea…
Discretization Invariant Networks for Learning Maps between Neural Fields
Clinton J. Wang, Polina Golland
With the emergence of powerful representations of continuous data in the form of neural fields, there is a need for discretization invariant learning: an approach for learning maps…
Pre-Trained Language Models for Interactive Decision-Making
Shuang Li, Xavier Puig, Chris Paxton +11
Language model (LM) pre-training is useful in many language processing tasks. But can pre-trained LMs be further leveraged for more general machine learning problems? We propose an…