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3D Fat/Water-Separated Liver T1 Mapping: A Study on the Influence of Fat and Repeatability

Accelerating Longitudinal Dynamic MRI by Exploiting Multi-Session Temporal Correlations

Author:Jingjia Chen  Daniel Sodickson  Li Feng  

Session Type:Power Pitch  

Session Date:Wednesday, 08 May 2024  

Session Name:Pitch: Image Reconstruction  

Program Number:1069  

Room Session:Power Pitch Theatre 1  

Institution:New York University Grossman School of Medicine  

Advanced Deep Learning Denoising for Accelerated 0.55T Prostate MRI

Free-breathing simultaneous quantification of fat fraction, R2, and T1 at 0.55T: Validation in a clinical cohort

Highly accelerated time-resolved 4D MRA using stack-of-stars golden-angle radial acquisition and subtraction-based subspace reconstruction

Introduction

Author:Li Feng  

Session Type:Oral  

Session Date:Thursday, 09 May 2024  

Session Name:AI-Empowered Image Planning, Quantification & Modeling  

Program Number:

Room Session:Hall 606  

Institution:New York University Grossman School of Medicine  

    Learning to synthesize MR contrasts using a self-supervised constrained contrastive learning approach

    Author:Lavanya Umapathy  Li Feng  Daniel Sodickson  

    Session Type:Oral  

    Session Date:Thursday, 09 May 2024  

    Session Name:Translation of AI into the Clinic  

    Program Number:1402  

    Room Session:Summit 2  

    Institution:New York University Grossman School of Medicine  

    Motion-Robust Multiparametric MRI of the Liver at 3T: Simultaneous Estimation of Water-Specific T1, PDFF, Motion-Resolved R2*, and QSM

    PET-MR compatible CEST method for imaging of Alzheimer’s Disease.

    Quantitative MRI with Automated Histogram Analysis Based on Self-Supervised Learning of Organ Segmentation: Demonstration for Liver T1 Mapping

    Self-supervised representational learning for automated risk assessment in longitudinal imaging

    SNAC-DL: Self-Supervised Network for Adaptive Convolutional Dictionary Learning of MRI Denoising

    Sub-Second GRASP-LLR DCE: Locally Low-Rank Subspace Constraint aided by Deep Learning

    Author:Eddy Solomon  Jonghyun Bae  Linda Moy  Laura Heacock  Li Feng  Sungheon Gene Kim  

    Session Type:Oral  

    Session Date:Tuesday, 07 May 2024  

    Session Name:Quantitative Image Reconstruction  

    Program Number:0626  

    Room Session:Hall 606  

    Institution:New York University  Weill Cornell Medicine  

    T1 Contrast-Augmented Single-Spoke Real-Time 4D MRI