AIMC Topic: Deep Learning

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Recurrent inference machines for reconstructing heterogeneous MRI data.

Medical image analysis
Deep learning allows for accelerated magnetic resonance image (MRI) reconstruction, thereby shortening measurement times. Rather than using sparsifying transforms, a prerequisite in Compressed Sensing (CS), suitable MRI prior distributions are learne...

A Deep Neural Network-Based Pain Classifier Using a Photoplethysmography Signal.

Sensors (Basel, Switzerland)
Side effects occur when excessive or low doses of analgesics are administered compared to the required amount to mediate the pain induced during surgery. It is important to accurately assess the pain level of the patient during surgery. We proposed a...

Gait-Based Diplegia Classification Using LSMT Networks.

Journal of healthcare engineering
Diplegia is a specific subcategory of the wide spectrum of motion disorders gathered under the name of cerebral palsy. Recent works proposed to use gait analysis for diplegia classification paving the way for automated analysis. A clinically establis...

Breast mass classification in sonography with transfer learning using a deep convolutional neural network and color conversion.

Medical physics
PURPOSE: We propose a deep learning-based approach to breast mass classification in sonography and compare it with the assessment of four experienced radiologists employing breast imaging reporting and data system 4th edition lexicon and assessment p...

Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers' Health Examination Data.

International journal of environmental research and public health
We aimed to use deep learning to detect tuberculosis in chest radiographs in annual workers' health examination data and compare the performances of convolutional neural networks (CNNs) based on images only (I-CNN) and CNNs including demographic vari...

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

Scientific reports
There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study ...

3D Human Pose Machines with Self-Supervised Learning.

IEEE transactions on pattern analysis and machine intelligence
Driven by recent computer vision and robotic applications, recovering 3D human poses has become increasingly important and attracted growing interests. In fact, completing this task is quite challenging due to the diverse appearances, viewpoints, occ...

A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.

NeuroImage
Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's disease (AD), while other MCI types tend to remain stable over-time and do not progress to AD. To identify and choose effective and personalized strategies to pr...

Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological Changes.

SLAS discovery : advancing life sciences R & D
The quantification and identification of cellular phenotypes from high-content microscopy images has proven to be very useful for understanding biological activity in response to different drug treatments. The traditional approach has been to use cla...

Automated analysis of cardiovascular magnetic resonance myocardial native T mapping images using fully convolutional neural networks.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) myocardial native T mapping allows assessment of interstitial diffuse fibrosis. In this technique, the global and regional T are measured manually by drawing region of interest in motion-corrected T...