AIMC Topic: Imaging, Three-Dimensional
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Deep learning for efficient reconstruction of highly accelerated 3D FLAIR MRI in neurological deficits.
Magma (New York, N.Y.)
Aug 30, 2024
OBJECTIVE: To compare compressed sensing (CS) and the Cascades of Independently Recurrent Inference Machines (CIRIM) with respect to image quality and reconstruction times when 12-fold accelerated scans of patients with neurological deficits are reco...
Reproducibility of Results
Aged
Young Adult
Adult
Male
Middle Aged
Deep Learning
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Humans
Signal-To-Noise Ratio
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White Matter
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Child, Preschool
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Imaging, Three-Dimensional
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Image Interpretation, Computer-Assisted
Artifacts
Cross-view discrepancy-dependency network for volumetric medical image segmentation.
Medical image analysis
Aug 30, 2024
The limited data poses a crucial challenge for deep learning-based volumetric medical image segmentation, and many methods have tried to represent the volume by its subvolumes (i.e., multi-view slices) for alleviating this issue. However, such method...
Deep-learning-based method for the segmentation of ureter and renal pelvis on non-enhanced CT scans.
Scientific reports
Aug 30, 2024
This study aimed to develop a deep-learning (DL) based method for three-dimensional (3D) segmentation of the upper urinary tract (UUT), including ureter and renal pelvis, on non-enhanced computed tomography (NECT) scans. A total of 150 NECT scans wit...
Deep Learning-Enhanced Accelerated 2D TSE and 3D Superresolution Dixon TSE for Rapid Comprehensive Knee Joint Assessment.
Investigative radiology
Aug 28, 2024
OBJECTIVES: The aim of this study was to evaluate the use of a multicontrast deep learning (DL)-reconstructed 4-fold accelerated 2-dimensional (2D) turbo spin echo (TSE) protocol and the feasibility of 3-dimensional (3D) superresolution reconstructio...
A comparison of machine learning methods for recovering noisy and missing 4D flow MRI data.
International journal for numerical methods in biomedical engineering
Aug 28, 2024
Experimental blood flow measurement techniques are invaluable for a better understanding of cardiovascular disease formation, progression, and treatment. One of the emerging methods is time-resolved three-dimensional phase-contrast magnetic resonance...
Neural shape completion for personalized Maxillofacial surgery.
Scientific reports
Aug 27, 2024
In this paper, we investigate the effectiveness of shape completion neural networks as clinical aids in maxillofacial surgery planning. We present a pipeline to apply shape completion networks to automatically reconstruct complete eumorphic 3D meshes...
A 3D Convolutional Neural Network Based on Non-enhanced Brain CT to Identify Patients with Brain Metastases.
Journal of imaging informatics in medicine
Aug 26, 2024
Dedicated brain imaging for cancer patients is seldom recommended in the absence of symptoms. There is increasing availability of non-enhanced CT (NE-CT) of the brain, mainly owing to a wider utilization of Positron Emission Tomography-CT (PET-CT) in...
Mandibular Gender Dimorphism: The Utility of Artificial Intelligence and Statistical Shape Modeling in Skeletal Facial Analysis.
Aesthetic plastic surgery
Aug 26, 2024
BACKGROUND: In gender-affirming surgery, facial skeletal dimorphism is an important topic for every craniofacial surgeon. Few cephalometric studies have assessed this topic; however, they fall short to provide skeletal contour insights that direct su...
Performance enhancement of deep learning based solutions for pharyngeal airway space segmentation on MRI scans.
Scientific reports
Aug 24, 2024
The automatic segmentation of the pharyngeal airway space has many potential medical use, one of which is to help facilitate the creation of the Tubingen Palatal Plate. Therefore, it is of great importance to understand which methods are suitable for...
Utilizing convolutional neural networks for discriminating cancer and stromal cells in three-dimensional cell culture images with nuclei counterstain.
Journal of biomedical optics
Aug 24, 2024
SIGNIFICANCE: Accurate cell segmentation and classification in three-dimensional (3D) images are vital for studying live cell behavior and drug responses in 3D tissue culture. Evaluating diverse cell populations in 3D cell culture over time necessita...
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