activity
20162023
most citedDynamic Neural Fields for Learning Atlases of 4D Fetal MRI Time-series

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV20233 cited

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…

cs.CV2023

Consistency Regularization Improves Placenta Segmentation in Fetal EPI MRI Time Series

Yingcheng Liu, Neerav Karani, Neel Dey +5

The placenta plays a crucial role in fetal development. Automated 3D placenta segmentation from fetal EPI MRI holds promise for advancing prenatal care. This paper proposes an effe…

cs.CV2023

AnyStar: Domain randomized universal star-convex 3D instance segmentation

Neel Dey, S. Mazdak Abulnaga, Benjamin Billot +4

Star-convex shapes arise across bio-microscopy and radiology in the form of nuclei, nodules, metastases, and other units. Existing instance segmentation networks for such structure…

eess.IV2022

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…

cs.CV20161 cited

Temporal Registration in In-Utero Volumetric MRI Time Series

Ruizhi Liao, Esra Turk, Miaomiao Zhang +4

We present a robust method to correct for motion and deformations for in-utero volumetric MRI time series. Spatio-temporal analysis of dynamic MRI requires robust alignment across…