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Imaging, Three-Dimensional

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Prediction of surgery-first approach orthognathic surgery using deep learning models.

International journal of oral and maxillofacial surgery
The surgery-first approach (SFA) orthognathic surgery can be beneficial due to reduced overall treatment time and earlier profile improvement. The objective of this study was to utilize deep learning to predict the treatment modality of SFA or the or...

Heart and great vessels segmentation in congenital heart disease via CNN and conditioned energy function postprocessing.

International journal of computer assisted radiology and surgery
PURPOSE: The segmentation of the heart and great vessels in CT images of congenital heart disease (CHD) is critical for the clinical assessment of cardiac anomalies and the diagnosis of CHD. However, the diverse types and abnormalities inherent in CH...

Identification of Root Canal Morphology in Fused-rooted Mandibular Second Molars From X-ray Images Based on Deep Learning.

Journal of endodontics
INTRODUCTION: Understanding the intricate anatomical morphology of fused-rooted mandibular second molars (MSMs) is essential for root canal treatment. The present study utilized a deep learning approach to identify the three-dimensional root canal mo...

Progress of Artificial Intelligence-Driven Solutions for Automated Segmentation of Dental Pulp Space on Cone-Beam Computed Tomography Images. A Systematic Review.

Journal of endodontics
INTRODUCTION: Automated segmentation of 3-dimensional pulp space on cone-beam computed tomography images presents a significant opportunity for enhancing diagnosis, treatment planning, and clinical education in endodontics. The aim of this systematic...

Deep Learning-Based Facial and Skeletal Transformations for Surgical Planning.

Journal of dental research
The increasing application of virtual surgical planning (VSP) in orthognathic surgery implies a critical need for accurate prediction of facial and skeletal shapes. The craniofacial relationship in patients with dentofacial deformities is still not u...

Patient-specific cerebral 3D vessel model reconstruction using deep learning.

Medical & biological engineering & computing
Three-dimensional vessel model reconstruction from patient-specific magnetic resonance angiography (MRA) images often requires some manual maneuvers. This study aimed to establish the deep learning (DL)-based method for vessel model reconstruction. T...

Development and evaluation of a deep learning framework for the diagnosis of malnutrition using a 3D facial points cloud: A cross-sectional study.

JPEN. Journal of parenteral and enteral nutrition
BACKGROUND: The feasibility of diagnosing malnutrition using facial features has been validated. A tool to integrate all facial features associated with malnutrition for disease screening is still demanded. This work aims to develop and evaluate a de...

3DVascNet: An Automated Software for Segmentation and Quantification of Mouse Vascular Networks in 3D.

Arteriosclerosis, thrombosis, and vascular biology
BACKGROUND: Analysis of vascular networks is an essential step to unravel the mechanisms regulating the physiological and pathological organization of blood vessels. So far, most of the analyses are performed using 2-dimensional projections of 3-dime...

Assessing the efficacy of 2D and 3D CNN algorithms in OCT-based glaucoma detection.

Scientific reports
Glaucoma is a progressive neurodegenerative disease characterized by the gradual degeneration of retinal ganglion cells, leading to irreversible blindness worldwide. Therefore, timely and accurate diagnosis of glaucoma is crucial, enabling early inte...

CMAN: Cascaded Multi-scale Spatial Channel Attention-guided Network for large 3D deformable registration of liver CT images.

Medical image analysis
Deformable image registration is an essential component of medical image analysis and plays an irreplaceable role in clinical practice. In recent years, deep learning-based registration methods have demonstrated significant improvements in convenienc...