AIMC Topic: Imaging, Three-Dimensional

Clear Filters Showing 1731 to 1740 of 1894 articles

Skeletal facial asymmetry: reliability of manual and artificial intelligence-driven analysis.

Dento maxillo facial radiology
OBJECTIVES: To compare artificial intelligence (AI)-driven web-based platform and manual measurements for analysing facial asymmetry in craniofacial CT examinations.

Machine learning assessment of dental age classification based on cone-beam CT images: a different approach.

Dento maxillo facial radiology
OBJECTIVES: Machine learning (ML) algorithms are a portion of artificial intelligence that may be used to create more accurate algorithmic procedures for estimating an individual's dental age or defining an age classification. This study aims to use ...

Research on the effectiveness of multi-view slice correction strategy based on deep learning in high pitch helical CT reconstruction.

Journal of X-ray science and technology
BACKGROUND: Recent studies have explored layered correction strategies, employing a slice-by-slice approach to mitigate the prominent limited-view artifacts present in reconstructed images from high-pitch helical CT scans. However, challenges persist...

Untrained Network for Super-resolution for Non-contrast-enhanced Wholeheart MRI Acquired using Cardiac-triggered REACT (SRNN-REACT).

Current medical imaging
BACKGROUND: Three-dimensional (3D) whole-heart magnetic resonance imaging (MRI) is an excellent tool to check the heart anatomy of patients with congenital and acquired heart disease. However, most 3D whole-heart MRI acquisitions take a long time to ...

DNeuroMAT: A Deep-Learning-Based Neuron Morphology Analysis Toolbox.

Methods in molecular biology (Clifton, N.J.)
Digital reconstruction of neuronal structures from 3D neuron microscopy images is critical for the quantitative investigation of brain circuits and functions. Currently, neuron reconstructions are mainly obtained by manual or semiautomatic methods. H...

A user-friendly deep learning application for accurate lung cancer diagnosis.

Journal of X-ray science and technology
BACKGROUND: Accurate diagnosis and subsequent delineated treatment planning require the experience of clinicians in the handling of their case numbers. However, applying deep learning in image processing is useful in creating tools that promise faste...

Software that combines deep learning, 3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Ultrasound is one of the non-invasive techniques that are used in clinical diagnostics of carotid artery disease.

Are multi-detector computed tomography and cone-beam computed tomography exams and software accurate to measure the upper airway? A systematic review.

European journal of orthodontics
BACKGROUND: Cone-beam computed tomography (CBCT) has several applications in various fields of dental medicine such as diagnosis and treatment planning. When compared to computed tomography (CT), CBCT's radiation exposure dose is decreased by 3%-20%....

Using a New Deep Learning Method for 3D Cephalometry in Patients With Hemifacial Microsomia.

Annals of plastic surgery
Deep learning algorithms based on automatic 3D cephalometric marking points about people without craniomaxillofacial deformities have achieved good results. However, there has been no previous report about hemifacial microsomia (HFM). The purpose of ...

[Application Value of Artificial Intelligence-assisted Three-dimensional Reconstruction in Planning Thoracoscopic Segmentectomy].

Zhongguo fei ai za zhi = Chinese journal of lung cancer
BACKGROUND: The three-dimensional (3D) can assist in planning lung segmentectomy. 3D reconstruction software based on artificial intelligence algorithm is gradually applied in clinic. The aim of this study was to evaluate the accuracy and safety of 3...