153 citations · 161 across the 7 of their papers we have counts for
7 papers
Ground tracking for improved landmine detection in a GPR system
Li Tang, Peter A. Torrione, Cihat Eldeniz +1
Ground penetrating radar (GPR) provides a promising technology for accurate subsurface object detection. In particular, it has shown promise for detecting landmines with low metal…
Self-Supervised Deep Equilibrium Models for Inverse Problems with Theoretical Guarantees
Weijie Gan, Chunwei Ying, Parna Eshraghi +7
Deep equilibrium models (DEQ) have emerged as a powerful alternative to deep unfolding (DU) for image reconstruction. DEQ models-implicit neural networks with effectively infinite…
SPICER: Self-Supervised Learning for MRI with Automatic Coil Sensitivity Estimation and Reconstruction
Yuyang Hu, Weijie Gan, Chunwei Ying +6
Deep model-based architectures (DMBAs) integrating physical measurement models and learned image regularizers are widely used in parallel magnetic resonance imaging (PMRI). Traditi…
Image Reconstruction for MRI using Deep CNN Priors Trained without Groundtruth
Weijie Gan, Cihat Eldeniz, Jiaming Liu +3
We propose a new plug-and-play priors (PnP) based MR image reconstruction method that systematically enforces data consistency while also exploiting deep-learning priors. Our prior…
Deformation-Compensated Learning for Image Reconstruction without Ground Truth
Weijie Gan, Yu Sun, Cihat Eldeniz +3
Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets. Recent work on Noise2Noise (N2N) has sho…
Deep Image Reconstruction using Unregistered Measurements without Groundtruth
Weijie Gan, Yu Sun, Cihat Eldeniz +3
One of the key limitations in conventional deep learning based image reconstruction is the need for registered pairs of training images containing a set of high-quality groundtruth…
RARE: Image Reconstruction using Deep Priors Learned without Ground Truth
Jiaming Liu, Yu Sun, Cihat Eldeniz +3
Regularization by denoising (RED) is an image reconstruction framework that uses an image denoiser as a prior. Recent work has shown the state-of-the-art performance of RED with le…