AIMC Topic: Imaging, Three-Dimensional

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High-resolution dynamic imaging of chromatin DNA communication using Oligo-LiveFISH.

Cell
Three-dimensional (3D) genome dynamics are crucial for cellular functions and disease. However, real-time, live-cell DNA visualization remains challenging, as existing methods are often confined to repetitive regions, suffer from low resolution, or r...

Localisation and classification of multi-stage caries on CBCT images with a 3D convolutional neural network.

Clinical oral investigations
OBJECTIVES: Dental caries remains a significant global health concern. Recognising the diagnostic potential of cone-beam computed tomography (CBCT) in caries assessment, this study aimed to develop an artificial intelligence (AI)-driven tool for accu...

Joint semi-supervised and contrastive learning enables domain generalization and multi-domain segmentation.

Medical image analysis
Despite their effectiveness, current deep learning models face challenges with images coming from different domains with varying appearance and content. We introduce SegCLR, a versatile framework designed to segment images across different domains, e...

Cross-institutional validation of a polar map-free 3D deep learning model for obstructive coronary artery disease prediction using myocardial perfusion imaging: insights into generalizability and bias.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep learning (DL) models for predicting obstructive coronary artery disease (CAD) using myocardial perfusion imaging (MPI) have shown potential for enhancing diagnostic accuracy. However, their ability to maintain consistent performance acr...

Skull CT metadata for automatic bone age assessment by using three-dimensional deep learning framework.

International journal of legal medicine
Bone age assessment (BAA) means challenging tasks in forensic science especially in some extreme situations like only skulls found. This study aimed to develop an accurate three-dimensional deep learning (DL) framework at skull CT metadata for BAA an...

A deep learning model for multiclass tooth segmentation on cone-beam computed tomography scans.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: Machine learning, a common artificial intelligence technology in medical image analysis, enables computers to learn statistical patterns from pairs of data and annotated labels. Supervised learning in machine learning allows the compute...

Method of Forearm Muscles 3D Modeling Using Robotic Ultrasound Scanning.

Sensors (Basel, Switzerland)
The accurate assessment of muscle morphology and function is crucial for medical diagnostics, rehabilitation, and biomechanical research. This study presents a novel methodology for constructing volumetric models of forearm muscles based on three-dim...

A Novel Hierarchical Cross-Stream Aggregation Neural Network for Semantic Segmentation of 3-D Dental Surface Models.

IEEE transactions on neural networks and learning systems
Accurate teeth delineation on 3-D dental models is essential for individualized orthodontic treatment planning. Pioneering works like PointNet suggest a promising direction to conduct efficient and accurate 3-D dental model analyses in end-to-end lea...

Predicting cell cycle stage from 3D single-cell nuclear-stained images.

Life science alliance
The cell cycle governs the proliferation of all eukaryotic cells. Profiling cell cycle dynamics is therefore central to basic and biomedical research. However, current approaches to cell cycle profiling involve complex interventions that may confound...