AIMC Topic: Neural Networks, Computer

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DeepAlign, a 3D alignment method based on regionalized deep learning for Cryo-EM.

Journal of structural biology
Cryo Electron Microscopy (Cryo-EM) is currently one of the main tools to reveal the structural information of biological specimens at high resolution. Despite the great development of the techniques involved to solve the biological structures with Cr...

MRI-Based Deep-Learning Method for Determining Glioma Promoter Methylation Status.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: () promoter methylation confers an improved prognosis and treatment response in gliomas. We developed a deep learning network for determining promoter methylation status using T2 weighted Images (T2WI) only.

Discovering Collective Variables of Molecular Transitions via Genetic Algorithms and Neural Networks.

Journal of chemical theory and computation
With the continual improvement of computing hardware and algorithms, simulations have become a powerful tool for understanding all sorts of (bio)molecular processes. To handle the large simulation data sets and to accelerate slow, activated transitio...

Automatic liver segmentation using 3D convolutional neural networks with a hybrid loss function.

Medical physics
PURPOSE: Automatic liver segmentation from abdominal computed tomography (CT) images is a fundamental task in computer-assisted liver surgery programs. Many liver segmentation algorithms are very sensitive to fuzzy boundaries and heterogeneous pathol...

Effects of Image Degradation and Degradation Removal to CNN-Based Image Classification.

IEEE transactions on pattern analysis and machine intelligence
Just like many other topics in computer vision, image classification has achieved significant progress recently by using deep learning neural networks, especially the Convolutional Neural Networks (CNNs). Most of the existing works focused on classif...

Orthogonal Deep Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
In this paper, we introduce the algorithms of Orthogonal Deep Neural Networks (OrthDNNs) to connect with recent interest of spectrally regularized deep learning methods. OrthDNNs are theoretically motivated by generalization analysis of modern DNNs, ...

Appearance and Pose-Conditioned Human Image Generation Using Deformable GANs.

IEEE transactions on pattern analysis and machine intelligence
In this paper, we address the problem of generating person images conditioned on both pose and appearance information. Specifically, given an image x of a person and a target pose P(x), extracted from an image x, we synthesize a new image of that per...

NRA-Net-Neg-Region Attention Network for Salient Object Detection with Gaze Tracking.

Sensors (Basel, Switzerland)
In this paper, we propose a detection method for salient objects whose eyes are focused on gaze tracking; this method does not require a device in a single image. A network was constructed using Neg-Region Attention (NRA), which predicts objects with...

Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolutional Neural Network.

Journal of medical systems
In this work, an attempt has been made to classify emotional states using electrodermal activity (EDA) signals and multiscale convolutional neural networks. For this, EDA signals are considered from a publicly available "A Dataset for Emotion Analysi...

Automatic attenuation map estimation from SPECT data only for brain perfusion scans using convolutional neural networks.

Physics in medicine and biology
In clinical brain SPECT, correction for photon attenuation in the patient is essential to obtain images which provide quantitative information on the regional activity concentration per unit volume (kBq.[Formula: see text]). This correction generally...