no code implementations • 26 Mar 2024 • Weijie Gan, Huidong Xie, Carl von Gall, Günther Platsch, Michael T. Jurkiewicz, Andrea Andrade, Udunna C. Anazodo, Ulugbek S. Kamilov, Hongyu An, Jorge Cabello
Anatomically guided PET reconstruction using MRI information has been shown to have the potential to improve PET image quality.
no code implementations • 30 Nov 2023 • Chicago Park, Shirin Shoushtari, Weijie Gan, Ulugbek S. Kamilov
This paper presents a theoretical explanation for the observed stability of PnP-ADMM based on the interpretation of the CNN prior as a minimum mean-squared error (MMSE) denoiser.
no code implementations • 29 Nov 2023 • Yuyang Hu, Satya V. V. N. Kothapalli, Weijie Gan, Alexander L. Sukstanskii, Gregory F. Wu, Manu Goyal, Dmitriy A. Yablonskiy, Ulugbek S. Kamilov
We introduce a new framework called DiffGEPCI for cross-modality generation in magnetic resonance imaging (MRI) using a 2. 5D conditional diffusion model.
no code implementations • 26 Nov 2023 • Zihao Zou, Jiaming Liu, Shirin Shoushtari, YuBo Wang, Weijie Gan, Ulugbek S. Kamilov
Face video restoration (FVR) is a challenging but important problem where one seeks to recover a perceptually realistic face videos from a low-quality input.
no code implementations • 7 Nov 2023 • Huidong Xie, Weijie Gan, Bo Zhou, Xiongchao Chen, Qiong Liu, Xueqi Guo, Liang Guo, Hongyu An, Ulugbek S. Kamilov, Ge Wang, Chi Liu
We extensively evaluated DDPET-3D on 100 patients with 6 different low-dose levels (a total of 600 testing studies), and demonstrated superior performance over previous diffusion models for 3D imaging problems as well as previous noise-aware medical image denoising models.
no code implementations • 3 Nov 2023 • Chicago Park, Weijie Gan, Zihao Zou, Yuyang Hu, Zhixin Sun, Ulugbek S. Kamilov
There is a growing interest in model-based deep learning (MBDL) for solving imaging inverse problems.
1 code implementation • 11 Oct 2023 • Weijie Gan, Qiuchen Zhai, Michael Thompson McCann, Cristina Garcia Cardona, Ulugbek S. Kamilov, Brendt Wohlberg
Ptychography is an imaging technique that captures multiple overlapping snapshots of a sample, illuminated coherently by a moving localized probe.
no code implementations • 6 Oct 2023 • Junhao Hu, Weijie Gan, Zhixin Sun, Hongyu An, Ulugbek S. Kamilov
A traditional DL approach to DIR is based on training a convolutional neural network (CNN) to estimate the registration field between two input images.
no code implementations • 26 Oct 2022 • Harry Gao, Weijie Gan, Zhixin Sun, Ulugbek S. Kamilov
Implicit neural representations (INR) have been recently proposed as deep learning (DL) based solutions for image compression.
no code implementations • 12 Oct 2022 • Xiaojian Xu, Weijie Gan, Satya V. V. N. Kothapalli, Dmitriy A. Yablonskiy, Ulugbek S. Kamilov
Quantitative MRI (qMRI) refers to a class of MRI methods for quantifying the spatial distribution of biological tissue parameters.
no code implementations • 7 Oct 2022 • Weijie Gan, Chunwei Ying, Parna Eshraghi, Tongyao Wang, Cihat Eldeniz, Yuyang Hu, Jiaming Liu, Yasheng Chen, Hongyu An, Ulugbek S. Kamilov
Our numerical results on in-vivo MRI data show that SelfDEQ leads to state-of-the-art performance using only undersampled and noisy training data.
no code implementations • 5 Oct 2022 • Yuyang Hu, Weijie Gan, Chunwei Ying, Tongyao Wang, Cihat Eldeniz, Jiaming Liu, Yasheng Chen, Hongyu An, Ulugbek S. Kamilov
However, estimation of accurate CSMs is a challenging problem when measurements are highly undersampled.
1 code implementation • 25 May 2022 • Jiaming Liu, Xiaojian Xu, Weijie Gan, Shirin Shoushtari, Ulugbek S. Kamilov
However, the dependence of the computational/memory complexity of the measurement models in PnP/RED on the total number of measurements leaves DEQ impractical for many imaging applications.
no code implementations • 10 Apr 2022 • Weijie Gan, Cihat Eldeniz, Jiaming Liu, Sihao Chen, Hongyu An, Ulugbek S. Kamilov
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.
1 code implementation • 28 Feb 2022 • Wentao Shangguan, Yu Sun, Weijie Gan, Ulugbek S. Kamilov
This paper considers the problem of temporal video interpolation, where the goal is to synthesize a new video frame given its two neighbors.
Ranked #1 on Video Frame Interpolation on Xiph 4k
1 code implementation • 3 Sep 2021 • Xiaojian Xu, Satya V. V. N. Kothapalli, Jiaming Liu, Sayan Kahali, Weijie Gan, Dmitriy A. Yablonskiy, Ulugbek S. Kamilov
LEARN-IMG performs motion correction on mGRE images and relies on the subsequent analysis for the estimation of $R_2^\ast$ maps, while LEARN-BIO directly performs motion- and $B0$-inhomogeneity-corrected $R_2^\ast$ estimation.
1 code implementation • 12 Jul 2021 • Weijie Gan, Yu Sun, Cihat Eldeniz, Jiaming Liu, Hongyu An, Ulugbek S. Kamilov
Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets.
1 code implementation • 22 Jan 2021 • Jiaming Liu, Yu Sun, Weijie Gan, Xiaojian Xu, Brendt Wohlberg, Ulugbek S. Kamilov
Deep unfolding networks have recently gained popularity in the context of solving imaging inverse problems.
no code implementations • 29 Sep 2020 • Weijie Gan, Yu Sun, Cihat Eldeniz, Jiaming Liu, Hongyu An, Ulugbek S. Kamilov
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 images.