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Deep learning-based measurement of isovolumic relaxation time from cardiovascular magnetic resonance long-axis cines: validation with pressure-derived IVRT

Barrientos L. et al, (2024)

Advancements in glioma segmentation: comparing the U-Net and DeconvNet models

Mohammed AA. and Gonzales RA., (2024), Journal of Emerging Investigators

Effects of data amount and variation in deep learning-based tuberculosis diagnosis in chest X-ray scans

Bhorkar A. and Gonzales RA., (2024), Journal of Emerging Investigators, 7

Lung cancer AI-based diagnosis through multi-modal integration of clinical and imaging data

Ulag AS. and Gonzales RA., (2024), Journal of Emerging Investigators, 7

Effects of software on myocardial T1 measurements: a 3 T multicentre single vendor phantom study

Atkinson D. et al, (2024)

dT1 maps: A novel approach for visualising myocardial stress without gadolinium-based contrast agents

Gonzales RA. et al, (2024)

Convolutional neural network-based analysis of pediatric chest X-ray images for pneumonia detection

Ma Y. and Gonzales RA., (2024), Journal of Emerging Investigators

Tricuspid valve flow measurement using a deep learning framework for automated valve‐tracking 2D phase contrast

Lamy J. et al, (2024), Magnetic Resonance in Medicine

Deep learning for automated insertion point annotation of CMR T1 maps

Gonzales RA. et al, (2024)

Automated CMR index of left ventricular diastolic function (e'): a validation study against echocardiography in the large-scale Beta3-LVH trial

Gonzales RA. et al, (2024)

Automated CMR Index of Left Ventricular Diastolic Function Post-acute Myocardial Infarction Provides Independent and Incremental Prediction of Long-term Prognosis When Added to Conventional Indices

Shanmuganathan M. et al, (2024), Journal of Cardiovascular Magnetic Resonance, 26, 100268 - 100268

Enhancing marine debris identification with convolutional neural networks

Wahlig V. and Gonzales RA., (2024), Journal of Emerging Investigators

Quality control-driven framework for reliable automated segmentation of cardiac magnetic resonance LGE and VNE images

Gonzales RA. et al, (2023)

TVnet: a deep-learning approach for enhanced right ventricular function analysis through tricuspid valve motion tracking

Gonzales RA. et al, (2023)

2.5D Flow MRI: 2D phase-contrast of the tricuspid valvular flow with automated valve-tracking

Lamy J. et al, (2023)

Deep learning for automated insertion point annotation of CMR late gadolinium enhancement and virtual native enhancement images

Gonzales RA. et al, (2023)

Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images.

Gonzales RA. et al, (2023), Front Cardiovasc Med, 10

Artificial Intelligence for Contrast-Free MRI: Scar Assessment in Myocardial Infarction Using Deep Learning-Based Virtual Native Enhancement.

Zhang Q. et al, (2022), Circulation, 146, 1492 - 1503

2.5D flow MRI of tricuspid valvular flow: An accurate automated valve-following phase-contrast approach

Lamy J. et al, (2022)

TVnet: automated global analysis of tricuspid valve plane motion in CMR long-axis cines with residual neural networks for assessment of right ventricular function

Gonzales RA. et al, (2022), European Heart Journal - Cardiovascular Imaging, 23

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