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While typical qualitative T1-weighted magnetic resonance images reflect scanner and protocol differences, quantitative T1 mapping aims to measure T1 independent of these effects. Changes in T1 in the brain reflect structural changes in…

We propose a deep learning-based approach that integrates MRI sequence parameters to improve the accuracy and generalizability of quantitative image synthesis from clinical weighted MRI. Our physics-driven neural network embeds MRI sequence…

Image and Video Processing · Electrical Eng. & Systems 2025-08-12 Lingjing Chen , Chengxiu Zhang , Yinqiao Yi , Yida Wang , Yang Song , Xu Yan , Shengfang Xu , Dalin Zhu , Mengqiu Cao , Yan Zhou , Chenglong Wang , Guang Yang

The 3D fast silent multi-parametric mapping sequence with zero echo time (MuPa-ZTE) is a novel quantitative MRI (qMRI) acquisition that enables nearly silent scanning by using a 3D phyllotaxis sampling scheme. MuPa-ZTE improves patient…

Cardiac T1 mapping provides critical quantitative insights into myocardial tissue composition, enabling the assessment of pathologies such as fibrosis, inflammation, and edema. However, the inherently dynamic nature of the heart imposes…

Image and Video Processing · Electrical Eng. & Systems 2025-12-09 Tamir Shor , Moti Freiman , Chaim Baskin , Alex Bronstein

In this paper we implemented the algorithm we developed in [1] called 3DPIFCM in a parallel environment by using CUDA on a GPU. In our previous work we introduced 3DPIFCM which performs segmentation of images in noisy conditions and uses…

Computer Vision and Pattern Recognition · Computer Science 2020-02-07 Arie Agranonik , Maya Herman , Mark Last

Purpose: The clinical feasibility and translation of many advanced quantitative MRI (qMRI) techniques are inhibited by their restriction to 'research mode', due to resource-intensive, offline parameter estimation. This work aimed to achieve…

This paper proposes a statistical framework to optimize and evaluate the MR parameter $T_1$ and $T_2$ mapping capabilities for quantitative MRI relaxometry approaches. This analysis explores the intrinsic MR parameter estimate precision per…

Signal Processing · Electrical Eng. & Systems 2020-01-03 Yang Liu , John R. Buck , Shaokuan Zheng

A rise in blood flow velocity variations (i.e., pulsatility) in the brain, caused by the stiffening of upstream arteries, is associated with cognitive impairment and neurodegenerative diseases. The study of this phenomenon requires…

Magnetic resonance spectroscopic imaging (MRSI) enables the simultaneous non-invasive acquisition of MR spectra from multiple spatial locations inside the brain. While 1H-MRSI is increasingly used in the human brain, it is not yet widely…

Quantitative MRI enables direct quantification of contrast agent concentrations in contrast-enhanced scans. However, the lengthy scan times required by conventional methods are inadequate for tracking contrast agent transport dynamically in…

Objective: We propose a method for the reconstruction of parameter-maps in Quantitative Magnetic Resonance Imaging (QMRI). Methods: Because different quantitative parameter-maps differ from each other in terms of local features, we propose…

Image and Video Processing · Electrical Eng. & Systems 2023-08-08 Andreas Kofler , Kirsten Miriam Kerkering , Laura Göschel , Ariane Fillmer , Cristoph Kolbitsch

The Spreading Projection Algorithm for Rapid K-space samplING, or SPARKLING, is an optimization-driven method that has been recently introduced for accelerated 2D T2*-w MRI using compressed sensing. It has then been extended to address 3D…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-26 Chaithya G R , Pierre Weiss , Guillaume Daval-Frérot , Aurélien Massire , Alexandre Vignaud , Philippe Ciuciu

To rapidly obtain high resolution T2, T2* and quantitative susceptibility mapping (QSM) source separation maps with whole-brain coverage and high geometric fidelity. We propose Blip Up-Down Acquisition for Spin And Gradient Echo imaging…

High-quality, multi-channel neural recording is indispensable for neuroscience research and clinical applications. Large-scale brain recordings often produce vast amounts of data that must be wirelessly transmitted for subsequent offline…

Hardware Architecture · Computer Science 2025-09-03 Adithya Krishna , Sohan Debnath , Madhuvanthi Srivatsav , André van Schaik , Mahesh Mehendale , Chetan Singh Thakur

Purpose: To evaluate a Deep-Learning-enhanced MUlti-PArametric MR sequence (DL-MUPA) for treatment response assessment for brain metastases patients undergoing stereotactic radiosurgery (SRS) and head-and-neck (HnN) cancer patients…

Purpose: To develop and validate a framework for rapid, accurate, and reproducible whole-brain, multi-pool chemical exchange saturation transfer (CEST) imaging at 3T, addressing challenges of long acquisition times and confounding factors.…

Medical Physics · Physics 2025-09-16 Yupeng Wu , Siyuan Fang , Siyuan Wang , Caixia Fu , Jianqi Li

Whole brain segmentation on a structural magnetic resonance imaging (MRI) is essential in non-invasive investigation for neuroanatomy. Historically, multi-atlas segmentation (MAS) has been regarded as the de facto standard method for whole…

Computer Vision and Pattern Recognition · Computer Science 2018-06-06 Yuankai Huo , Zhoubing Xu , Katherine Aboud , Prasanna Parvathaneni , Shunxing Bao , Camilo Bermudez , Susan M. Resnick , Laurie E. Cutting , Bennett A. Landman

Purpose: To provide real-time quantitative organ-specific information - specifically placental and brain T2* - to allow optimization of the MR examination to the individual patient. Methods: A FIRE-based real-time setup segmenting placenta…

Quantitative angiography (QA) in two dimensions has been instrumental in assessing neurovascular contrast flow patterns, aiding disease severity and treatment outcome evaluations. However, QA requires high spatio-temporal resolution,…

Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) represent two mainstream model quantization approaches. However, PTQ often leads to unacceptable performance degradation in quantized models, while QAT imposes…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Xinhao Wang , Zhiwei Lin , Zhongyu Xia , Yongtao Wang