AIMC Topic: Imaging, Three-Dimensional

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Advantages of fully automated AI-enhanced algorithm (5D CNS+™) for generating a fetal neurosonogram in clinical routine.

Journal of perinatal medicine
OBJECTIVES: The objective was to demonstrate superiority of a fully vs. semi-automated approach (5D CNS+™) and to verify operators could handle and benefit from a fully automated rendering volumetric datasets to generate a complete fetal neurosonogra...

Evaluating Undersampling Schemes and Deep Learning Reconstructions for High-Resolution 3D Double Echo Steady State Knee Imaging at 7 T: A Comparison Between GRAPPA, CAIPIRINHA, and Compressed Sensing.

Investigative radiology
OBJECTIVE: The 3-dimensional (3D) double echo steady state (DESS) magnetic resonance imaging sequence can image knee cartilage with high, isotropic resolution, particularly at high and ultra-high field strengths. Advanced undersampling techniques wit...

Distinct 3-Dimensional Morphologies of Arthritic Knee Anatomy Exist: CT-Based Phenotyping Offers Outlier Detection in Total Knee Arthroplasty.

The Journal of bone and joint surgery. American volume
BACKGROUND: There is no foundational classification that 3-dimensionally characterizes arthritic anatomy to preoperatively plan and postoperatively evaluate total knee arthroplasty (TKA). With the advent of computed tomography (CT) as a preoperative ...

A simple and effective approach for body part recognition on CT scans based on projection estimation.

Scientific reports
It is well known that machine learning models require a high amount of annotated data to obtain optimal performance. Labelling Computed Tomography (CT) data can be a particularly challenging task due to its volumetric nature and often missing and/or ...

TomoGRAF: An X-ray physics-driven generative radiance field framework for extremely sparse view CT reconstruction.

PloS one
OBJECTIVES: Computed tomography (CT) provides high spatial-resolution visualization of 3D structures for various applications. Traditional analytical/iterative CT reconstruction algorithms require hundreds of angular samplings, a condition may not be...

AlzFormer: Multi-modal framework for Alzheimer's classification using MRI and graph-embedded demographics guided by adaptive attention gating.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Alzheimer's disease (AD) is the most common neurodegenerative progressive disorder and the fifth-leading cause of death in older people. The detection of AD is a very challenging task for clinicians and radiologists due to the complex nature of this ...

AI-assisted 3D versus conventional 2D preoperative planning in total hip arthroplasty for Crowe type II-IV high hip dislocation: a two-year retrospective study.

Journal of orthopaedic surgery and research
BACKGROUND: With the growing complexity of total hip arthroplasty (THA) for high hip dislocation (HHD), artificial intelligence (AI)-assisted three-dimensional (3D) preoperative planning has emerged as a promising tool to enhance surgical accuracy. T...

An effective flowchart for multimodal brain tumor binary classification with ranked 3D texture features.

Scientific reports
Brain tumors have complex structures, and their shape, density, and size can vary widely. Consequently, their accurate classification, which involves identifying features that best describe the tumor data, is challenging. Using classical 2D texture f...

HSPC-Net: A hierarchical shape-preserving completion network for machine part point cloud completion.

PloS one
With the continuous advancement of 3D scanning technology, point cloud data of mechanical components has found widespread applications in industrial design, manufacturing, and repair. However, due to limitations in scanning precision and acquisition ...