AI Medical Compendium Topic:
Imaging, Three-Dimensional

Clear Filters Showing 541 to 550 of 1615 articles

Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm.

PloS one
INTRODUCTION: Rotator cuff tear (RCT) is a challenging and common musculoskeletal disease. Magnetic resonance imaging (MRI) is a commonly used diagnostic modality for RCT, but the interpretation of the results is tedious and has some reliability issu...

Diagnostic performance of deep learning-based reconstruction algorithm in 3D MR neurography.

Skeletal radiology
OBJECTIVE: The study aims to evaluate the diagnostic performance of deep learning-based reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and lumbosacral plexus.

Automated large volume sample preparation for vEM.

Methods in cell biology
New developments in electron microscopy technology, improved efficiency of detectors, and artificial intelligence applications for data analysis over the past decade have increased the use of volume electron microscopy (vEM) in the life sciences fiel...

Deep learning-based reconstruction and 3D hybrid profile order technique for MRCP at 3T: evaluation of image quality and acquisition time.

European radiology
OBJECTIVES: To evaluate the image quality of the 3D hybrid profile order technique and deep-learning-based reconstruction (DLR) for 3D magnetic resonance cholangiopancreatography (MRCP) within a single breath-hold (BH) at 3 T magnetic resonance imagi...

Robot-assisted ultrasound reconstruction for spine surgery: from bench-top to pre-clinical study.

International journal of computer assisted radiology and surgery
PURPOSE: Robot-assisted ultrasound (rUS) systems have already been used to provide non-radiative three-dimensional (3D) reconstructions that form the basis for guiding spine surgical procedures. Despite promising studies on this technology, there are...

Precise Brain-shift Prediction by New Combination of W-Net Deep Learning for Neurosurgical Navigation.

Neurologia medico-chirurgica
Brain tissue deformation during surgery significantly reduces the accuracy of image-guided neurosurgeries. We generated updated magnetic resonance images (uMR) in this study to compensate for brain shifts after dural opening using a convolutional neu...

Eliminating the need for manual segmentation to determine size and volume from MRI. A proof of concept on segmenting the lateral ventricles.

PloS one
Manual segmentation, which is tedious, time-consuming, and operator-dependent, is currently used as the gold standard to validate automatic and semiautomatic methods that quantify geometries from 2D and 3D MR images. This study examines the accuracy ...

Denoising diffusion probabilistic models for 3D medical image generation.

Scientific reports
Recent advances in computer vision have shown promising results in image generation. Diffusion probabilistic models have generated realistic images from textual input, as demonstrated by DALL-E 2, Imagen, and Stable Diffusion. However, their use in m...

Accurate gingival segmentation from 3D images with artificial intelligence: an animal pilot study.

Progress in orthodontics
BACKGROUND: Gingival phenotype plays an important role in dental diagnosis and treatment planning. Traditionally, determining the gingival phenotype is done by manual probing of the gingival soft tissues, an invasive and time-consuming procedure. Thi...