AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Imaging, Three-Dimensional

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Accuracy Comparison between Robot-Assisted Dental Implant Placement and Static/Dynamic Computer-Assisted Implant Surgery: A Systematic Review and Meta-Analysis of In Vitro Studies.

Medicina (Kaunas, Lithuania)
: The present systematic review and meta-analysis undertake a comparison of studies that examine the accuracy of robot-assisted dental implant placement in relation to static computer-assisted implant surgery (SCAIS), dynamic computer-assisted implan...

Evaluation of mediastinal lymph node segmentation of heterogeneous CT data with full and weak supervision.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate lymph node size estimation is critical for staging cancer patients, initial therapeutic management, and assessing response to therapy. Current standard practice for quantifying lymph node size is based on a variety of criteria that use uni-d...

Cellstitch: 3D cellular anisotropic image segmentation via optimal transport.

BMC bioinformatics
BACKGROUND: Spatial mapping of transcriptional states provides valuable biological insights into cellular functions and interactions in the context of the tissue. Accurate 3D cell segmentation is a critical step in the analysis of this data towards u...

Three-dimensional spine reconstruction from biplane radiographs using convolutional neural networks.

Medical engineering & physics
PURPOSE: The purpose of this study was to develop and evaluate a deep learning network for three-dimensional reconstruction of the spine from biplanar radiographs.

Deep Learning-Based Synthetic TOF-MRA Generation Using Time-Resolved MRA in Fast Stroke Imaging.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Time-resolved MRA enables collateral evaluation in acute ischemic stroke with large-vessel occlusion; however, a low SNR and spatial resolution impede the diagnosis of vascular occlusion. We developed a CycleGAN-based deep lea...

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation.

Nature methods
Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convoluti...

Deep-learning-based image quality enhancement of CT-like MR imaging in patients with suspected traumatic shoulder injury.

European journal of radiology
PURPOSE: To evaluate the diagnostic performance of CT-like MR images reconstructed with an algorithm combining compressed sense (CS) with deep learning (DL) in patients with suspected osseous shoulder injury compared to conventional CS-reconstructed ...

Artificial intelligence-based forensic sex determination of East Asian cadavers from skull morphology.

Scientific reports
Identification of unknown cadavers is an important task for forensic scientists. Forensic scientists attempt to identify skeletal remains based on factors including age, sex, and dental treatment remains. Forensic scientists commonly consider skull o...

Generative adversarial networks in dental imaging: a systematic review.

Oral radiology
OBJECTIVES: This systematic review on generative adversarial network (GAN) architectures for dental image analysis provides a comprehensive overview to readers regarding current GAN trends in dental imagery and potential future applications.

Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning.

Scientific reports
Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma surgery. Advances in deep learning technology provide good insights into trauma surgery over manual diagnosis. This study demonstrates the application ...