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About my Research

I am an Assistant Professor at the Athinoula A. Martinos Center for Biomedical Imaging at the Department of Radiology at Massachusetts General Hospital / Harvard Medical School and Member of the Affiliated Harvard-MIT HST Faculty at the department of Health, Sciences and Technology (HST) of the Massachusetts Institute of Technology (MIT).  My interests focus in improving non-invasive molecular imaging quantification with combined PET/MRI scanners. In particular most of my research is applied to brain and cardiovascular imaging to provide useful diagnostic tools for early detection of cardiovascular disease and brain disorders.

Since my initial steps in medical imaging at the University of Cambridge, UK, I have been working on improving PET image quantification, mostly using MR-based techniques. Among them, I implemented for the first time a partial volume effect correction method for cardiovascular imaging. I have also focused on improving simultaneous PET/MR image quantification by applying MR-based attenuation correction (AC) for PET imaging. Currently more than a dozen international groups have implemented this method for brain AC. I am currently leading a novel line of research using artificial intelligence on cardiovascular applications, that aims to provide improved cardiac motion detection and quantification.

Algorithm Development  Brain 
Cardiovascular Disease / Disorders

 Cardiovascular System     Data Science

Machine Learning   Molecular Imaging  Multimodal Imaging  PET    PET/MRI 

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Publications

1. Izquierdo-Garcia D, Davies JR, Graves MJ, Rudd JH, Gillard JH, Weissberg PL, Fryer TD, Warburton EA. Comparison of methods for magnetic resonance-guided [18-F]fluorodeoxyglucose positron emission tomography in human carotid arteries:  reproducibility, partial volume correction, and correlation between methods. Stroke. 2009 Jan;40(1):86-93.

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2. Izquierdo-Garcia D, Hansen AE, Förster S, Benoit D, Schachoff S, Fürst S, Chen KT, Chonde DB, Catana C. An SPM8-based approach for attenuation correction combining segmentation and nonrigid template formation: application to simultaneous PET/MR brain imaging. J Nucl Med. 2014 Nov;55(11):1825-30.

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3. Morales M*, Izquierdo-Garcia D*, Aganj I, Kalpathy-Cramer J, Rosen BR, Catana C. Implementation and Validation of a 3D Cardiac Motion Estimation Network (CarMEN). Radiology: Artificial Intelligence. In press. 2019.

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4. Morales M, van den Boomen M, Nguyen C, Kalpathy-Cramer J, Rosen BR, Stultz CM, Catana C* and Izquierdo-Garcia D*. DeepStrain: a Deep Learning workflow for the automated characterization of cardiac mechanic. BioRXiv. 2021.

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