AIMC Topic: Imaging, Three-Dimensional

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Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder.

Tomography (Ann Arbor, Mich.)
According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults suffer from attention deficit hyperactivity disorder (ADHD). This disorder can have significant negative consequences on people's lives, particularly c...

Rethinking femoral neck anteversion assessment: a novel automated 3D CT method compared to traditional manual techniques.

BMC musculoskeletal disorders
PURPOSE: To evaluate the accuracy and reliability of a novel automated 3D CT-based method for measuring femoral neck anteversion (FNA) compared to three traditional manual methods.

An automated cascade framework for glioma prognosis via segmentation, multi-feature fusion and classification techniques.

Biomedical physics & engineering express
Glioma is one of the most lethal types of brain tumors, accounting for approximately 33% of all diagnosed brain tumor cases. Accurate segmentation and classification are crucial for precise glioma characterization, emphasizing early detection of mali...

Three-Dimensional Reconstruction of Serial Block-Face Scanning Electron Microscopy Using Semantic Segmentation based on Semi-Supervised Deep Learning.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
Serial block-face scanning electron microscopy (SBF-SEM) is employed to achieve high-resolution volume reconstructions and detailed ultrastructural analyses of complex organelles. The performance of SBF-SEM is evaluated according to the accuracy of s...

Artificial intelligence-based pulmonary vessel segmentation: an opportunity for automated three-dimensional planning of lung segmentectomy.

Interdisciplinary cardiovascular and thoracic surgery
OBJECTIVES: This study aimed to develop an automated method for pulmonary artery and vein segmentation in both left and right lungs from computed tomography (CT) images using artificial intelligence (AI). The segmentations were evaluated using PulmoS...

brain2print AI powered web tool for creating 3D printable brain models.

Scientific reports
We introduce brain2print, a web-based application that converts T1-weighted MRI scans into 3D printable models. By leveraging artificial intelligence (AI), brain2print performs all computations directly on the user's device, preserving privacy while ...

The role of the sacroiliac joint in sex estimation: Analysis of morphometry and variation types using machine learning techniques.

Legal medicine (Tokyo, Japan)
This study aimed to evaluate the potential of machine learning algorithms in sex estimation by going beyond the traditional two-dimensional (2D) measurements of the pelvic bone, predominantly preferred in sex prediction, by including measurement data...

Anatomy-derived 3D Aortic Hemodynamics Using Fluid Physics-informed Deep Learning.

Radiology
Background Four-dimensional (4D) flow MRI provides assessment of thoracic aorta hemodynamic measures that are increasingly recognized as important biomarkers for risk assessment. However, long acquisition times and cumbersome data analysis limit wide...

Artificial intelligence driven 3D reconstruction for enhanced lung surgery planning.

Nature communications
The increasing complexity of lung surgeries necessitates the need for enhanced imaging support to improve the precision and efficiency of preoperative planning. Despite the promise of 3D reconstruction, clinical adoption remains limited due to time c...

LLMER: Crafting Interactive Extended Reality Worlds with JSON Data Generated by Large Language Models.

IEEE transactions on visualization and computer graphics
The integration of Large Language Models (LLMs) like GPT-4 with Extended Reality (XR) technologies offers the potential to build truly immersive XR environments that interact with human users through natural language, e.g., generating and animating 3...