Mary Robakowski

AutoCMR: democratizing access to cardiac MRI with a push-button 4D isotropic whole thoracic automated exam

Danielle Kara, Ashmita Deb, Hoa Quang Le, Mary Robakowski et autres

Motivation: With complicated protocols requiring specialized training for both acquisition and analysis, access to cardiac magnetic resonance (CMR) is generally limited to academic hospitals. Goal(s): Our goal is to provide a push-button CMR exam (AutoCMR) with 4D isotropic cine and delayed enhancement …

Democratizing cardiac imaging with an automated magnetic resonance exam

Danielle Kara, Ashmita Deb, Hoa Quang Le, Daniel Wee et autres

us (code pays fourni par la source)

The effect of magnetic resonance image resolution and amount of segmentation smoothing on aortic computational fluid dynamics

Mary Robakowski, Mohsen Darayi, Danielle Kara, Yuncong Mao et autres

us (code pays fourni par la source)

Global heart function: Automated characterization of cardiac spatiotemporal features from isotropic 4D whole thoracic automated cardiac MRI (AutoCMR)

Hoa Quang Le, Ashmita Deb, Makiya Nakashima, Kashyap Bodi et autres

us (code pays fourni par la source)

AutoCMR: Democratizing access to cardiac MRI with a push-button, 4D isotropic whole thoracic automated exam

Danielle Kara, Ashmita Deb, Mary Robakowski, Hoa Quang Le et autres

us (code pays fourni par la source)

Isotropic 4D whole thoracic automated cardiac mri (autocmr) for non-invasive computational simulation of patient-specific left ventricular dynamics

Mohsen Darayi, Mary Robakowski, Ojas Y. Potdar, Danielle Kara et autres

us (code pays fourni par la source)

AI‐Powered Multimodal Modeling of Personalized Hemodynamics in Aortic Stenosis

Çağlar Öztürk, Daniel H. Pak, Luca Rosalia, Debkalpa Goswami et autres

Aortic stenosis (AS) is the most common valvular heart disease in developed countries. High-fidelity preclinical models can improve AS management by enabling therapeutic innovation, early diagnosis, and tailored treatment planning. However, their use is currently limited by complex workflows necessitating lengthy expert-driven …

gb, us (code pays fourni par la source)

Deep Learning-Based High Frequency Constrained Fast Image Reconstruction for 4D Cardiac MRI

Ashmita Deb, Danielle Kara, Mary Robakowski, Ojas Y. Potdar et autres

Motivation: Online image reconstructions for prospectively undersampled cardiac MRI data are noisy as the naïve approach fails to remove undersampling artifacts. Compressed sensing (CS) reconstruction reduces artifacts but is time and memory intensive, making it an offline reconstruction option only. Goal(s): Our …

AI-powered multimodal modeling of personalized hemodynamics in aortic stenosis

Çağlar Öztürk, Daniel H. Pak, Luca Rosalia, Debkalpa Goswami et autres

Aortic stenosis (AS) is the most common valvular heart disease in developed countries. High-fidelity preclinical models can improve AS management by enabling therapeutic innovation, early diagnosis, and tailored treatment planning. However, their use is currently limited by complex workflows necessitating lengthy expert-driven …