AIMC Topic: Imaging, Three-Dimensional

Clear Filters Showing 941 to 950 of 1894 articles

Design of MRI structured spiking neural networks and learning algorithms for personalized modelling, analysis, and prediction of EEG signals.

Scientific reports
This paper proposes a novel method and algorithms for the design of MRI structured personalized 3D spiking neural network models (MRI-SNN) for a better analysis, modeling, and prediction of EEG signals. It proposes a novel gradient-descent learning a...

End-to-end deep learning nonrigid motion-corrected reconstruction for highly accelerated free-breathing coronary MRA.

Magnetic resonance in medicine
PURPOSE: To develop an end-to-end deep learning technique for nonrigid motion-corrected (MoCo) reconstruction of ninefold undersampled free-breathing whole-heart coronary MRA (CMRA).

Patient-to-robot registration: The fate of robot-assisted stereotaxy.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Robot-assisted stereotaxy (RAS) promises higher stereotactic accuracy (SA) and time efficiency (TE) than frame-based stereotaxy. However, both aspects are attributed to the problem of patient-to-robot registration.

QTTNet: Quantized tensor train neural networks for 3D object and video recognition.

Neural networks : the official journal of the International Neural Network Society
Relying on the rapidly increasing capacity of computing clusters and hardware, convolutional neural networks (CNNs) have been successfully applied in various fields and achieved state-of-the-art results. Despite these exciting developments, the huge ...

An Analysis of the Vulnerability of Two Common Deep Learning-Based Medical Image Segmentation Techniques to Model Inversion Attacks.

Sensors (Basel, Switzerland)
Recent research in computer vision has shown that original images used for training of deep learning models can be reconstructed using so-called inversion attacks. However, the feasibility of this attack type has not been investigated for complex 3D ...

Detecting pelvic fracture on 3D-CT using deep convolutional neural networks with multi-orientated slab images.

Scientific reports
Pelvic fracture is one of the leading causes of death in the elderly, carrying a high risk of death within 1 year of fracture. This study proposes an automated method to detect pelvic fractures on 3-dimensional computed tomography (3D-CT). Deep convo...

D-UNet: A Dimension-Fusion U Shape Network for Chronic Stroke Lesion Segmentation.

IEEE/ACM transactions on computational biology and bioinformatics
Assessing the location and extent of lesions caused by chronic stroke is critical for medical diagnosis, surgical planning, and prognosis. In recent years, with the rapid development of 2D and 3D convolutional neural networks (CNN), the encoder-decod...

Preclinical evaluation of a markerless, real-time, augmented reality guidance system for robot-assisted radical prostatectomy.

International journal of computer assisted radiology and surgery
PURPOSE: Intra-operative augmented reality (AR) during surgery can mitigate incomplete cancer removal by overlaying the anatomical boundaries extracted from medical imaging data onto the camera image. In this paper, we present the first such complete...

Searching collaborative agents for multi-plane localization in 3D ultrasound.

Medical image analysis
3D ultrasound (US) has become prevalent due to its rich spatial and diagnostic information not contained in 2D US. Moreover, 3D US can contain multiple standard planes (SPs) in one shot. Thus, automatically localizing SPs in 3D US has the potential t...

Resection of Intracranial Tumors with a Robotic-Assisted Digital Microscope: A Preliminary Experience with Robotic Scope.

World neurosurgery
BACKGROUND: Magnified intraoperative visualization is of paramount importance during microsurgical procedures. Although the introduction of the operating microscope represented one of the most relevant innovations in modern neurosurgery, surgical vis...