Advances in experimental medicine and biology
35508872
A new application of ultrasonography has been emerging in the bone quantitative ultrasound arena in the last twenty years: cortical bone characterization using axial transmission ultrasound (ATU). Although challenged by the complicated cortical tissu...
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
35765697
Bone milling is one of the most important and sensitive biomechanical processes in the field of medical engineering. This process is used in orthopedic surgery, dentistry, treatment of fractures, and bone biopsy. The use of automatic numerical contro...
BACKGROUND: The superiorities in proximal facet joint protection of robot-assisted (RA) pedicle screw placement and screw implantation via the cortical bone trajectory (CBT) have rarely been compared. Moreover, findings on the screw accuracy of both ...
BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent of bone mineral density (BMD). Ultrashort echo time (UTE) MRI techniques of measuring cortical bone...
PURPOSE: The purpose of this study was to evaluate the ability to depict in vivo bone vascularization using ultra-high-resolution (UHR) computed tomography (CT) with deep learning reconstruction (DLR) and hybrid iterative reconstruction algorithm, co...
Robot-assisted (RA) technology has been shown to be a safe aid in spine surgery, this meta-analysis aims to compare surgical parameters and clinical indexes between robot-assisted cortical bone trajectory (CBT) and fluoroscopy-assisted (FA) cortical ...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
39217957
This study presents a novel methodology for optimizing the number of Raman spectra required per sample for human bone compositional analysis. The methodology integrates Artificial Neural Network (ANN) and Monte Carlo Simulation (MCS). We demonstrate ...
OBJECTIVES: This study developed and evaluated a two-stage deep learning-based system for automatic segmentation of mandibular cortical bone, mandibular cancellous bone, maxillary cortical bone and maxillary cancellous bone on cone beam computed tomo...
OBJECTIVES: To develop a deep learning-based automatic segmentation method for cortex and marrow in mandibular condyle on cone-beam computed tomography (CBCT) images and explore its clinical application.
Recent advancements in deep learning have significantly enhanced the segmentation of high-resolution microcomputed tomography (µCT) bone scans. In this paper, we present the dual-branch attention-based hybrid network (DBAHNet), a deep learning archit...