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Deep Learning-based image reconstruction improves CEST MRI

Early prediction of pathologic complete response to neoadjuvant systemic therapy for triple-negative breast cancer using deep learning

Improving the Bloch Fitting Method for the Analysis of acidoCEST MRI

Making CEST a Quantitative & Standardized Methodology

Author:Mark Pagel  

Session Type:Plenary Session  

Session Date:Monday, 17 May 2021  

Topic:Monday Plenary  

Session Name:CEST-MRI Challenges & Promises  

Program Number:

Room Session:Concurrent 1  

Institution:MD Anderson Cancer Center  

    Radiomics model based on MAGIC acquisition for predicting neoadjuvant systemic treatment response in triple-negative breast cancer.

    Targeted Contrast Agents

    Author:Mark Pagel  

    Session Type:Weekend Course  

    Session Date:Sunday, 16 May 2021  

    Topic:Multimodal Preclinical Imaging  

    Session Name:Multimodal Preclinical Imaging  

    Program Number:

    Room Session:Concurrent 3  

    Institution:MD Anderson Cancer Center  

      The video domain transfer deep learning network with error correction for Dixon Imaging with consistent slice-to-slice water and fat separation