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Multivariate time-series modeling and forecasting is an important problem with numerous applications. Traditional approaches such as VAR (vector auto-regressive) models and more recent approaches such as RNNs (recurrent neural networks) are…

Machine Learning · Computer Science 2017-09-12 Hardik Goel , Igor Melnyk , Arindam Banerjee

We propose a unified deep meta-learning framework for accelerated magnetic resonance imaging (MRI) that jointly addresses multi-coil reconstruction and cross-modality synthesis. Motivated by the limitations of conventional methods in…

Optimization and Control · Mathematics 2026-03-10 Merham Fouladvand , Peuroly Batra

High resolution automotive radar sensors are required in order to meet the high bar of autonomous vehicles needs and regulations. However, current radar systems are limited in their angular resolution causing a technological gap. An…

Signal Processing · Electrical Eng. & Systems 2022-06-07 Itai Orr , Moshik Cohen , Harel Damari , Meir Halachmi , Zeev Zalevsky

Portable low-field magnetic resonance imaging (MRI) systems have gained renewed interest owing to their cost effectiveness and point-of-care imaging capabilities. Yet, portable MRI systems suffer from relatively low signal-to-noise ratio…

We introduce a fast iterative non-local shrinkage algorithm to recover MRI data from undersampled Fourier measurements. This approach is enabled by the reformulation of current non-local schemes as an alternating algorithm to minimize a…

Computer Vision and Pattern Recognition · Computer Science 2014-05-22 Yasir Q. Moshin , Greg Ongie , Mathews Jacob

We provide a novel new approach for aligning geometric models using a dual graph structure where local features are mapping probabilities. Alignment of non-rigid structures is one of the most challenging computer vision tasks due to the…

Computer Vision and Pattern Recognition · Computer Science 2021-12-15 Dvir Ginzburg , Dan Raviv

The use of digitally reconstructed radiographs (DRRs) to solve inverse problems such as slice-to-volume registration and 3D reconstruction is well-studied in preoperative settings. In intraoperative imaging, the utility of DRRs is limited…

Computer Vision and Pattern Recognition · Computer Science 2022-08-29 Vivek Gopalakrishnan , Polina Golland

Purpose: An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T2 mapping from single-shot OverLapping-Echo Detachment (OLED) planar imaging. Methods:…

Computer Vision and Pattern Recognition · Computer Science 2017-08-18 Congbo Cai , Yiqing Zeng , Chao Wang , Shuhui Cai , Jun Zhang , Zhong Chen , Xinghao Ding , Jianhui Zhong

Dynamic Magnetic Resonance Imaging (MRI) exhibits transformation symmetries, including spatial rotation symmetry within individual frames and temporal symmetry along the time dimension. Explicit incorporation of these symmetry priors in the…

Image and Video Processing · Electrical Eng. & Systems 2025-06-13 Yuliang Zhu , Jing Cheng , Qi Xie , Zhuo-Xu Cui , Qingyong Zhu , Yuanyuan Liu , Xin Liu , Jianfeng Ren , Chengbo Wang , Dong Liang

Estimating $T_2$ relaxation time distributions from multi-echo $T_2$-weighted MRI ($T_2W$) data can provide valuable biomarkers for assessing inflammation, demyelination, edema, and cartilage composition in various pathologies, including…

Signal Processing · Electrical Eng. & Systems 2023-05-19 Hadas Ben-Atya , Moti Freiman

Dynamic magnetic resonance imaging (dMRI) captures temporally-resolved anatomy but is often challenged by limited sampling and motion-induced artifacts. Conventional motion-compensated reconstructions typically rely on pre-estimated optical…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Baoqing Li , Yuanyuan Liu , Congcong Liu , Qingyong Zhu , Jing Cheng , Yihang Zhou , Hao Chen , Zhuo-Xu Cui , Dong Liang

We present a fast iterative FFT-based reconstruction algorithm that allows for non- parallel redshift-space distortions (RSD). We test our algorithm on both N-body dark matter simulations and mock distributions of galaxies designed to…

Cosmology and Nongalactic Astrophysics · Physics 2015-08-17 Angela Burden , Will J. Percival , Cullan Howlett

Recent research efforts in optical computing have gravitated towards developing optical neural networks that aim to benefit from the processing speed and parallelism of optics/photonics in machine learning applications. Among these…

Optics · Physics 2020-12-25 Deniz Mengu , Yair Rivenson , Aydogan Ozcan

Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic information, but some modalities are limited by the long scanning time. To accelerate the whole acquisition process, MRI reconstruction of one modality from highly…

Image and Video Processing · Electrical Eng. & Systems 2025-01-09 Hao Zhang , Qi Wang , Jun Shi , Shihui Ying , Zhijie Wen

MRI with multiple protocols is commonly used for diagnosis, but it suffers from a long acquisition time, which yields the image quality vulnerable to say motion artifacts. To accelerate, various methods have been proposed to reconstruct…

Image and Video Processing · Electrical Eng. & Systems 2020-04-09 Bo Zhou , S. Kevin Zhou

Great successes have been achieved using deep learning techniques for image super-resolution (SR) with fixed scales. To increase its real world applicability, numerous models have also been proposed to restore SR images with arbitrary scale…

Image and Video Processing · Electrical Eng. & Systems 2022-09-28 Zhihong Pan , Baopu Li , Dongliang He , Wenhao Wu , Errui Ding

Deep neural networks (DNNs) have become the driving force behind recent artificial intelligence (AI) research. An important problem with implementing a neural network is the design of its architecture. Typically, such an architecture is…

Neural and Evolutionary Computing · Computer Science 2021-03-30 Shayan Hassantabar , Zeyu Wang , Niraj K. Jha

We introduce a deep learning (DL) framework for inverse problems in imaging, and demonstrate the advantages and applicability of this approach in passive synthetic aperture radar (SAR) image reconstruction. We interpret image recon-…

Computer Vision and Pattern Recognition · Computer Science 2018-03-14 Bariscan Yonel , Eric Mason , Birsen Yazıcı

Device-to-device (D2D) communications offers high spectral efficiency, low energy consumption and transmission latency. However, one of the main limitations of D2D communications is co-channel interference from underlaying wireless system.…

Signal Processing · Electrical Eng. & Systems 2023-08-02 Wali Ullah Khan , Eva Lagunas , Asad Mahmood , Zain Ali , Symeon Chatzinotas , Björn Ottersten

We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study of moving organs such as the heart. Existing reconstruction…

Image and Video Processing · Electrical Eng. & Systems 2021-01-26 Jaejun Yoo , Kyong Hwan Jin , Harshit Gupta , Jerome Yerly , Matthias Stuber , Michael Unser