1 citations · 1 across the 4 of their papers we have counts for
4 papers
SynStitch: a Self-Supervised Learning Network for Ultrasound Image Stitching Using Synthetic Training Pairs and Indirect Supervision
Xing Yao, Runxuan Yu, Dewei Hu +10
Ultrasound (US) image stitching can expand the field-of-view (FOV) by combining multiple US images from varied probe positions. However, registering US images with only partially o…
PRISM Lite: A lightweight model for interactive 3D placenta segmentation in ultrasound
Hao Li, Baris Oguz, Gabriel Arenas +6
Placenta volume measured from 3D ultrasound (3DUS) images is an important tool for tracking the growth trajectory and is associated with pregnancy outcomes. Manual segmentation is…
Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound images
Hao Li, Baris Oguz, Gabriel Arenas +6
Placenta volume measurement from 3D ultrasound images is critical for predicting pregnancy outcomes, and manual annotation is the gold standard. However, such manual annotation is…
SAM3D: Zero-Shot Semi-Automatic Segmentation in 3D Medical Images with the Segment Anything Model
Trevor J. Chan, Aarush Sahni, Yijin Fang +4
We introduce SAM3D, a new approach to semi-automatic zero-shot segmentation of 3D images building on the existing Segment Anything Model. We achieve fast and accurate segmentations…