AIMC Topic: Imaging, Three-Dimensional
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Automatic segmentation and volumetric analysis of intracranial hemorrhages in brain CT images.
European journal of radiology
Jan 27, 2025
BACKGROUND: Intracranial hemorrhages (ICH) are life-threatening conditions that require rapid detection and precise subtype classification. Automated segmentation and volumetric analysis using deep learning can enhance clinical decision-making.
A deep learning pipeline for three-dimensional brain-wide mapping of local neuronal ensembles in teravoxel light-sheet microscopy.
Nature methods
Jan 27, 2025
Teravoxel-scale, cellular-resolution images of cleared rodent brains acquired with light-sheet fluorescence microscopy have transformed the way we study the brain. Realizing the potential of this technology requires computational pipelines that gener...
Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.
Tomography (Ann Arbor, Mich.)
Jan 27, 2025
BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thick...
PMFSNet: Polarized multi-scale feature self-attention network for lightweight medical image segmentation.
Computer methods and programs in biomedicine
Jan 25, 2025
BACKGROUND AND OBJECTIVES: Current state-of-the-art medical image segmentation methods prioritize precision but often at the expense of increased computational demands and larger model sizes. Applying these large-scale models to the relatively limite...
A platform combining automatic segmentation and automatic measurement of the maxillary sinus and adjacent structures.
Clinical oral investigations
Jan 25, 2025
OBJECTIVES: To develop a platform including a deep convolutional neural network (DCNN) for automatic segmentation of the maxillary sinus (MS) and adjacent structures, and automatic algorithms for measuring 3-dimensional (3D) clinical parameters.
Clinically oriented automatic three-dimensional enamel segmentation via deep learning.
BMC oral health
Jan 24, 2025
BACKGROUND: Establishing accurate, reliable, and convenient methods for enamel segmentation and analysis is crucial for effectively planning endodontic, orthodontic, and restorative treatments, as well as exploring the evolutionary patterns of mammal...
Leveraging labelled data knowledge: A cooperative rectification learning network for semi-supervised 3D medical image segmentation.
Medical image analysis
Jan 22, 2025
Semi-supervised 3D medical image segmentation aims to achieve accurate segmentation using few labelled data and numerous unlabelled data. The main challenge in the design of semi-supervised learning methods consists in the effective use of the unlabe...
Endovascular robotics: technical advances and future directions.
Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Jan 21, 2025
Endovascular interventions excel in treating cardiovascular diseases in a minimally invasive manner, showing improved outcomes over open techniques. However, challenges related to precise navigation - still relying on 2D fluoroscopy - persist. This r...
Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study.
Scientific reports
Jan 21, 2025
The hyoid bone has been identified as sexually dimorphic in various populations. The current study is a forerunner analysis that used three-dimensional multidetector computed tomography (3D MDCT) images of the hyoid bone to examine sexual dimorphism ...
A multi-modal dental dataset for semi-supervised deep learning image segmentation.
Scientific data
Jan 20, 2025
In response to the increasing prevalence of dental diseases, dental health, a vital aspect of human well-being, warrants greater attention. Panoramic X-ray images (PXI) and Cone Beam Computed Tomography (CBCT) are key tools for dentists in diagnosing...
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