AIMC Topic: Imaging, Three-Dimensional

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Towards markerless robot-assisted navigation with 2D-3D registration for anterior cruciate ligament reconstruction.

Computers in biology and medicine
Conventional navigation frameworks in orthopaedic surgery use optical tracking to localize objects in the surgical workspace. This approach demonstrates high precision, but requires implanting optical tracking arrays in patient anatomy, leading to in...

Contribution of Labrum and Cartilage to Joint Surface in Different Hip Deformities: An Automatic Deep Learning-Based 3-Dimensional Magnetic Resonance Imaging Analysis.

The American journal of sports medicine
BACKGROUND: Multiple 2-dimensional magnetic resonance imaging (MRI) studies have indicated that the size of the labrum adjusts in response to altered joint loading. In patients with hip dysplasia, it tends to increase as a compensatory mechanism for ...

Enhancing biliary tract cancer diagnosis using AI-driven 3D optical diffraction tomography.

Methods (San Diego, Calif.)
Biliary tract cancer is associated with distinct metabolic alterations, particularly in lipid metabolism. This study aimed to classify biliary tract cancer cells automatically based on lipid droplet (LD) characteristics using three-dimensional (3D) o...

Preoperative Prognosis Prediction for Pathological Stage IA Lung Adenocarcinoma: 3D-Based Consolidation Tumor Ratio is Superior to 2D-Based Consolidation Tumor Ratio.

Academic radiology
BACKGROUND: The two-dimensional computed tomography measurement of the consolidation tumor ratio (2D-CTR) has limitations in the prognostic evaluation of early-stage lung adenocarcinoma: the measurement is subject to inter-observer variability and la...

A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation.

Scientific reports
In clinical medicine, a reliable and resource-friendly computer-aided diagnosis (CAD) method for brain tumor segmentation is essential to enhance diagnostic accuracy and therapeutic outcomes, particularly in regions with uneven healthcare resource di...

AI-powered segmentation of bifid mandibular canals using CBCT.

BMC oral health
OBJECTIVE: Accurate segmentation of the mandibular and bifid canals is crucial in dental implant planning to ensure safe implant placement, third molar extractions and other surgical interventions. The objective of this study is to develop and valida...

Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision.

Scientific reports
Craniofacial morphometrics in sharks provide crucial insights into evolutionary history, geographical variation, sexual dimorphism, and developmental patterns. However, the fragile cartilaginous nature of shark craniofacial skeleton poses significant...

Enhancing Lesion Detection in Inflammatory Myelopathies: A Deep Learning-Reconstructed Double Inversion Recovery MRI Approach.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: The imaging of inflammatory myelopathies has advanced significantly across time, with MRI techniques playing a pivotal role in enhancing lesion detection. However, the impact of deep learning (DL)-based reconstruction on 3D do...

Accelerating 3D radial MPnRAGE using a self-supervised deep factor model.

Magnetic resonance in medicine
PURPOSE: To develop a self-supervised and memory-efficient deep learning image reconstruction method for 4D non-Cartesian MRI with high resolution and a large parametric dimension.

Automated landmark-based mid-sagittal plane: reliability for 3-dimensional mandibular asymmetry assessment on head CT scans.

Clinical oral investigations
OBJECTIVE: The determination of the mid-sagittal plane (MSP) on three-dimensional (3D) head imaging is key to the assessment of facial asymmetry. The aim of this study was to evaluate the reliability of an automated landmark-based MSP to quantify man...