AIMC Topic: Breath Holding

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Deep-learning based surface region selection for deep inspiration breath hold (DIBH) monitoring in left breast cancer radiotherapy.

Physics in medicine and biology
Deep inspiration breath hold (DIBH) with surface supervising is a common technique for cardiac dose reduction in left breast cancer radiotherapy. Surface supervision accuracy relies on the characteristics of surface region. In this study, a convoluti...

Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning-proof of concept in congenital heart disease.

Magnetic resonance in medicine
PURPOSE: Real-time assessment of ventricular volumes requires high acceleration factors. Residual convolutional neural networks (CNN) have shown potential for removing artifacts caused by data undersampling. In this study, we investigated the ability...

Application of deep learning techniques for breath-hold, high-precision T2-weighted magnetic resonance imaging of the abdomen.

Abdominal radiology (New York)
PURPOSE: To evaluate the feasibility of a high-precision single-shot fast spin-echo (SS-FSE) sequence using the deep learning-based Precise IQ Engine (PIQE) algorithm in comparison with standard SS-FSE for T2-weighted MR imaging of the abdomen, and t...

Present and Future Innovations in AI and Cardiac MRI.

Radiology
Cardiac MRI is used to diagnose and treat patients with a multitude of cardiovascular diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and long acquisition protocols limit the specialty and restrain its impact on ...