activity
20192022
most citedRARE: Image Reconstruction using Deep Priors Learned without Ground Truth

153 citations · 172 across the 8 of their papers we have counts for

collaborators

8 papers

eess.IV2022★ 2 cited

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…

eess.IV2022★ 1 cited

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…

physics.med-ph2022

Synthetic PET via Domain Translation of 3D MRI

Abhejit Rajagopal, Yutaka Natsuaki, Kristen Wangerin +7

Historically, patient datasets have been used to develop and validate various reconstruction algorithms for PET/MRI and PET/CT. To enable such algorithm development, without the ne…

eess.IV2022★ 1 cited

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…

eess.IV2021

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…

eess.IV2020★ 4 cited

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…

eess.IV2019★ 153 cited

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…

physics.med-ph2019★ 11 cited

Bone Material Analogues for PET/MRI Phantoms

Dharshan Chandramohan, Peng Cao, Misung Han +6

Purpose: To develop bone material analogues that can be used in construction of phantoms for simultaneous PET/MRI systems. Methods: Plaster was used as the basis for the bone mater…