1 citations · 1 across the 1 of their papers we have counts for
8 papers
DDR-Net: Dividing and Downsampling Mixed Network for Diffeomorphic Image Registration
Ankita Joshi, Yi Hong
Deep diffeomorphic registration faces significant challenges for high-dimensional images, especially in terms of memory limits. Existing approaches either downsample original image…
MDA-Net: Multi-Dimensional Attention-Based Neural Network for 3D Image Segmentation
Rutu Gandhi, Yi Hong
Segmenting an entire 3D image often has high computational complexity and requires large memory consumption; by contrast, performing volumetric segmentation in a slice-by-slice man…
ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly Segmentation
Raunak Dey, Yi Hong
We introduce a neural network framework, utilizing adversarial learning to partition an image into two cuts, with one cut falling into a reference distribution provided by the user…
Hybrid Cascaded Neural Network for Liver Lesion Segmentation
Raunak Dey, Yi Hong
Automatic liver lesion segmentation is a challenging task while having a significant impact on assisting medical professionals in the designing of effective treatment and planning…
SA-Net: Deep Neural Network for Robot Trajectory Recognition from RGB-D Streams
Nihal Soans, Ehsan Asali, Yi Hong +1
Learning from demonstration (LfD) and imitation learning offer new paradigms for transferring task behavior to robots. A class of methods that enable such online learning require t…
Predictive Image Regression for Longitudinal Studies with Missing Data
Sharmin Pathan, Yi Hong
In this paper, we propose a predictive regression model for longitudinal images with missing data based on large deformation diffeomorphic metric mapping (LDDMM) and deep neural ne…