Search Results for author:
Found 5 papers, 2 papers with code
Whole-examination AI estimation of fetal biometrics from 20-week ultrasound scans
We use a Bayesian method to estimate the true value of each biometric from a large number of measurements and probabilistically reject outliers.
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
In this paper, we propose a general Riemannian formulation of the pose estimation problem.
3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images
We extensively evaluate the effectiveness of our approach quantitatively on simulated Magnetic Resonance Imaging (MRI), fetal brain imagery with synthetic motion and further demonstrate qualitative results on real fetal MRI data where our method is integrated into a full reconstruction and motion compensation pipeline.
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion
Our approach is attractive in challenging imaging scenarios, where significant subject motion complicates reconstruction performance of 3D volumes from 2D slice data.
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging
Fast imaging is required for targets that move to avoid motion artefacts.
