Publications by authors named "Jose de Arcos"
Article Synopsis
- The study aimed to compare the image quality and visibility of lesions in zero echo time (ZTE) MRI using a deep learning (DL) algorithm against conventional reconstruction methods, and to evaluate DL ZTE's effectiveness in assessing bone loss for shoulder instability compared to CT scans.
- Forty-four patients with shoulder instability underwent both ZTE MRI and CT scans, with images evaluated by two radiologists for clarity, resolution, and how well they showed lesions, using a rating scale.
- Results indicated that DL ZTE MRI images had superior resolution and showed lesions more clearly than conventional methods, with excellent agreement between DL ZTE and CT scans for measuring bone parameters.
Article Synopsis
- - A new low-rank reconstruction technique has been introduced to fill in missing samples during the dead-time gap in Zero Echo Time (ZTE) imaging.
- - The method treats the missing data as an inverse problem, and tests show that it performs better than traditional methods when evaluated through simulations and in vivo experiments.
- - This approach successfully reconstructs images artifact-free for dead-time gaps of up to 4 Nyquist dwells, improving imaging bandwidth effectiveness compared to standard algebraic and parallel imaging techniques.
Purpose: To evaluate the feasibility and utility of a deep learning (DL)-based reconstruction for improving the SNR of hyperpolarized Xe lung ventilation MRI.
Methods: Xe lung ventilation MRI data acquired from patients with asthma and/or chronic obstructive pulmonary disease (COPD) were retrospectively reconstructed with a commercial DL reconstruction pipeline at five different denoising levels. Quantitative imaging metrics of lung ventilation including ventilation defect percentage (VDP) and ventilation heterogeneity index (VH) were compared between each set of DL-reconstructed images and alternative denoising strategies including: filtering, total variation denoising and higher-order singular value decomposition.
Background: Changes in brain stiffness can be an important biomarker for neurological disease. Magnetic resonance elastography (MRE) quantifies tissue stiffness, but the results vary between acquisition and reconstruction methods.
Purpose: To measure MRE repeatability and estimate the effect of different reconstruction methods and varying data quality on estimated brain stiffness.
Purpose: We designed and built dedicated active magnetic resonance (MR)-tracked (MRTR) stylets. We explored the role of MRTR in a prospective clinical trial.
Methods And Materials: Eleven gynecologic cancer patients underwent MRTR to rapidly optimize interstitial catheter placement.