AIMC Topic: Imaging, Three-Dimensional

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Zygomatic implant placement using a robot-assisted flapless protocol: proof of concept.

International journal of oral and maxillofacial surgery
Robotic assistance can help in physically guiding the drilling trajectory during zygomatic implant positioning. A new robot-assisted strategy for a flapless zygomatic implant placement protocol is reported here. In this protocol, a preoperative compu...

Using Simulated Training Data of Voxel-Level Generative Models to Improve 3D Neuron Reconstruction.

IEEE transactions on medical imaging
Reconstructing neuron morphologies from fluorescence microscope images plays a critical role in neuroscience studies. It relies on image segmentation to produce initial masks either for further processing or final results to represent neuronal morpho...

GRASPNET: Fast spatiotemporal deep learning reconstruction of golden-angle radial data for free-breathing dynamic contrast-enhanced magnetic resonance imaging.

NMR in biomedicine
The purpose of the current study was to develop a deep learning technique called Golden-angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic contrast-enhanced 4D MRI acquired with golden-angle radial k-space trajectories...

Quantifying Valve Regurgitation Using 3-D Doppler Ultrasound Images and Deep Learning.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Accurate quantification of cardiac valve regurgitation jets is fundamental for guiding treatment. Cardiac ultrasound is the preferred diagnostic tool, but current methods for measuring the regurgitant volume (RVol) are limited by low accuracy and hig...

MR-self Noise2Noise: self-supervised deep learning-based image quality improvement of submillimeter resolution 3D MR images.

European radiology
OBJECTIVES: The study aimed to develop a deep neural network (DNN)-based noise reduction and image quality improvement by only using routine clinical scans and evaluate its performance in 3D high-resolution MRI.

Preliminary study of the accuracy and safety of robot-assisted mandibular distraction osteogenesis with electromagnetic navigation in hemifacial microsomia using rabbit models.

Scientific reports
This study aimed to investigate the accuracy and safety of mandibular osteotomy and distraction device positioning in distraction osteogenesis assisted by an electromagnetic navigation surgical robot. Twelve New Zealand white rabbits were randomly di...

Deep learning-based detection algorithm for brain metastases on black blood imaging.

Scientific reports
Brain metastases (BM) are the most common intracranial tumors, and their prevalence is increasing. High-resolution black-blood (BB) imaging was used to complement the conventional contrast-enhanced 3D gradient-echo imaging to detect BM. In this study...

Monitoring Amyloidogenesis with a 3D Deep-Learning-Guided Biolaser Imaging Array.

Nano letters
Amyloidogenesis is a critical hallmark for many neurodegenerative diseases and drug screening; however, identifying intermediate states of protein aggregates at an earlier stage remains challenging. Herein, we developed a peptide-encapsulated droplet...

DeepProjection: specific and robust projection of curved 2D tissue sheets from 3D microscopy using deep learning.

Development (Cambridge, England)
The efficient extraction of image data from curved tissue sheets embedded in volumetric imaging data remains a serious and unsolved problem in quantitative studies of embryogenesis. Here, we present DeepProjection (DP), a trainable projection algorit...

Rapid 3D breath-hold MR cholangiopancreatography using deep learning-constrained compressed sensing reconstruction.

European radiology
OBJECTIVES: To compare the image quality of three-dimensional breath-hold magnetic resonance cholangiopancreatography with deep learning-based compressed sensing reconstruction (3D DL-CS-MRCP) to those of 3D breath-hold MRCP with compressed sensing (...