AIMC Topic: Imaging, Three-Dimensional

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Automatic 3-D Lamina Curve Extraction From Freehand 3-D Ultrasound Data Using Sequential Localization Recurrent Convolutional Networks.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Freehand 3-D ultrasound imaging is emerging as a promising modality for regular spine exams due to its noninvasiveness and affordability. The laminae landmarks play a critical role in depicting the 3-D shape of the spine. However, the extraction of t...

CT ventilation images produced by a 3D neural network show improvement over the Jacobian and HU DIR-based methods to predict quantized lung function.

Medical physics
BACKGROUND: Radiation-induced pneumonitis affects up to 33% of non-small cell lung cancer (NSCLC) patients, with fatal pneumonitis occurring in 2% of patients. Pneumonitis risk is related to the dose and volume of lung irradiated. Clinical radiothera...

Generative modeling of the Circle of Willis using 3D-StyleGAN.

NeuroImage
The circle of Willis (CoW) is a network of cerebral arteries with significant inter-individual anatomical variations. Deep learning has been used to characterize and quantify the status of the CoW in various applications for the diagnosis and treatme...

AI-driven segmentation of the pulp cavity system in mandibular molars on CBCT images using convolutional neural networks.

Clinical oral investigations
OBJECTIVE: To develop and validate an artificial intelligence (AI)-driven tool for automated segmentation of the pulp cavity system of mandibular molars on cone-beam computed tomography (CBCT) images.

Reconstructing 3D histological structures using machine learning (artificial intelligence) algorithms.

Pathologie (Heidelberg, Germany)
BACKGROUND: Histomorphometry is currently the gold standard for bone microarchitectural examinations. This relies on two-dimensional (2D) sections to deduce the spatial properties of structures. Micromorphometric parameters are calculated from these ...

CIS-UNet: Multi-class segmentation of the aorta in computed tomography angiography via context-aware shifted window self-attention.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatments for aortic diseases. Accurate 3D segmentation of the aorta and its branches is crucial for interventions, as inaccurate segmentation can lead to ...

Overcoming the preferred-orientation problem in cryo-EM with self-supervised deep learning.

Nature methods
While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the 'preferred' orientation problem) remains a complication for most specimens. Existing ...

Recognition of autism in subcortical brain volumetric images using autoencoding-based region selection method and Siamese Convolutional Neural Network.

International journal of medical informatics
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects social interactions and behavior. Accurate and early diagnosis of ASD is still challenging even with the improvements in neuroimaging technology and machine lea...

Attention 3D UNET for dose distribution prediction of high-dose-rate brachytherapy of cervical cancer: Intracavitary applicators.

Journal of applied clinical medical physics
BACKGROUND: Formulating a clinically acceptable plan within the time-constrained clinical setting of brachytherapy poses challenges to clinicians. Deep learning based dose prediction methods have shown favorable solutions for enhancing efficiency, bu...

Comparison of different acceleration factors of artificial intelligence-compressed sensing for brachial plexus MRI imaging: scanning time and image quality.

BMC medical imaging
BACKGROUND: 3D brachial plexus MRI scanning is prone to examination failure due to the lengthy scan times, which can lead to patient discomfort and motion artifacts. Our purpose is to investigate the efficacy of artificial intelligence-assisted compr...