AIMC Topic: Deep Learning

Clear Filters Showing 22411 to 22420 of 28423 articles

Reconstructing faces from fMRI patterns using deep generative neural networks.

Communications biology
Although distinct categories are reliably decoded from fMRI brain responses, it has proved more difficult to distinguish visually similar inputs, such as different faces. Here, we apply a recently developed deep learning system to reconstruct face im...

Recomputation of the Dense Layers for Performance Improvement of DCNN.

IEEE transactions on pattern analysis and machine intelligence
Gradient descent optimization of learning has become a paradigm for training deep convolutional neural networks (DCNN). However, utilizing other learning strategies in the training process of the DCNN has rarely been explored by the deep learning (DL...

Adaptive Feature Recombination and Recalibration for Semantic Segmentation With Fully Convolutional Networks.

IEEE transactions on medical imaging
Fully convolutional networks have been achieving remarkable results in image semantic segmentation, while being efficient. Such efficiency results from the capability of segmenting several voxels in a single forward pass. So, there is a direct spatia...

Cerebral microbleed detection using Susceptibility Weighted Imaging and deep learning.

NeuroImage
Detecting cerebral microbleeds (CMBs) is important in diagnosing a variety of diseases including dementia, stroke and traumatic brain injury. However, manual detection of CMBs can be time-consuming and prone to errors, whereas the current automatic a...

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

Nature medicine
With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in the United States. Lung cancer screening using low-dose computed tomography has been shown to reduce mortality by 20-43% and is now included in US scree...

Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia.

PloS one
Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning have been successfully used to detect ventricular fibrillation (V...

Video-based surgical skill assessment using 3D convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: A profound education of novice surgeons is crucial to ensure that surgical interventions are effective and safe. One important aspect is the teaching of technical skills for minimally invasive or robot-assisted procedures. This includes the ...

Domain Progressive 3D Residual Convolution Network to Improve Low-Dose CT Imaging.

IEEE transactions on medical imaging
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly increased noise and artifacts, which might lower the judgment accura...

Identification of clathrin proteins by incorporating hyperparameter optimization in deep learning and PSSM profiles.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Clathrin is an adaptor protein that serves as the principal element of the vesicle-coating complex and is important for the membrane cleavage to dispense the invaginated vesicle from the plasma membrane. The functional loss...

Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies.

Virchows Archiv : an international journal of pathology
Histopathologic grading of prostate cancer using Gleason patterns (GPs) is subject to a large inter-observer variability, which may result in suboptimal treatment of patients. With the introduction of digitization and whole-slide images of prostate b...