AIMC Topic: Imaging, Three-Dimensional

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Deep learning-based motion tracking using ultrasound images.

Medical physics
PURPOSE: Ultrasound (US) imaging is an established imaging modality capable of offering video-rate volumetric images without ionizing radiation. It has the potential for intra-fraction motion tracking in radiation therapy. In this study, a deep learn...

Three-Dimensional Visualization of the Podocyte Actin Network Using Integrated Membrane Extraction, Electron Microscopy, and Machine Learning.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Actin stress fibers are abundant in cultured cells, but little is known about them . In podocytes, much evidence suggests that mechanobiologic mechanisms underlie podocyte shape and adhesion in health and in injury, with structural change...

Research on the Characteristics of Food Impaction with Tight Proximal Contacts Based on Deep Learning.

Computational and mathematical methods in medicine
OBJECTIVE: Based on deep learning, the characteristics of food impaction with tight proximal contacts were studied to guide the subsequent clinical treatment of occlusal adjustment. At the same time, digital model building, software measurement, and ...

Evolutionary Deep Attention Convolutional Neural Networks for 2D and 3D Medical Image Segmentation.

Journal of digital imaging
Developing a convolutional neural network (CNN) for medical image segmentation is a complex task, especially when dealing with the limited number of available labelled medical images and computational resources. This task can be even more difficult i...

Recycling diagnostic MRI for empowering brain morphometric research - Critical & practical assessment on learning-based image super-resolution.

NeuroImage
Preliminary studies have shown the feasibility of deep learning (DL)-based super-resolution (SR) technique for reconstructing thick-slice/gap diagnostic MR images into high-resolution isotropic data, which would be of great significance for brain res...

Study on 3D Image Reconstruction Model of Sparring Action Based on Graph Neural Network (GNN).

Computational intelligence and neuroscience
With the advent of the information age, human demand for information is increasing day by day. The emergence of the concept of big data has triggered a new round of technological revolution, and visual information plays an important role in informati...

Real-time 3D motion estimation from undersampled MRI using multi-resolution neural networks.

Medical physics
PURPOSE: To enable real-time adaptive magnetic resonance imaging-guided radiotherapy (MRIgRT) by obtaining time-resolved three-dimensional (3D) deformation vector fields (DVFs) with high spatiotemporal resolution and low latency (  ms). Theory and M...

Robot-Assisted SpiderMass for Real-Time Topography Mass Spectrometry Imaging.

Analytical chemistry
Mass spectrometry imaging (MSI) has shown to bring invaluable information for biological and clinical applications. However, conventional MSI is generally performed from tissue sections. Here, we developed a novel MS-based method for mass spectrome...

Performance evaluation in [18F]Florbetaben brain PET images classification using 3D Convolutional Neural Network.

PloS one
High accuracy has been reported in deep learning classification for amyloid brain scans, an important factor in Alzheimer's disease diagnosis. However, the possibility of overfitting should be considered, as this model is fitted with sample data. The...

A Liver Segmentation Method Based on the Fusion of VNet and WGAN.

Computational and mathematical methods in medicine
Accurate segmentation of liver images is an essential step in liver disease diagnosis, treatment planning, and prognosis. In recent years, although liver segmentation methods based on 2D convolutional neural networks have achieved good results, there...