AIMC Topic: Deep Learning

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Associated Learning: Decomposing End-to-End Backpropagation Based on Autoencoders and Target Propagation.

Neural computation
Backpropagation (BP) is the cornerstone of today's deep learning algorithms, but it is inefficient partially because of backward locking, which means updating the weights of one layer locks the weight updates in the other layers. Consequently, it is ...

Elastic Registration-driven Deep Learning for Longitudinal Assessment of Systemic Sclerosis Interstitial Lung Disease at CT.

Radiology
Background Longitudinal follow-up of interstitial lung diseases (ILDs) at CT mainly relies on the evaluation of the extent of ILD, without accounting for lung shrinkage. Purpose To develop a deep learning-based method to depict worsening of ILD based...

LMI-DForest: A deep forest model towards the prediction of lncRNA-miRNA interactions.

Computational biology and chemistry
The interactions between miRNAs and long non-coding RNAs (lncRNAs) are subject to intensive recent studies due to its critical role in gene regulations. Computational prediction of lncRNA-miRNA interactions has become a popular alternative strategy t...

Deep learning for identifying corneal diseases from ocular surface slit-lamp photographs.

Scientific reports
To demonstrate the identification of corneal diseases using a novel deep learning algorithm. A novel hierarchical deep learning network, which is composed of a family of multi-task multi-label learning classifiers representing different levels of eye...

Image segmentation of plexiform neurofibromas from a deep neural network using multiple b-value diffusion data.

Scientific reports
We assessed the accuracy of semi-automated tumor volume maps of plexiform neurofibroma (PN) generated by a deep neural network, compared to manual segmentation using diffusion weighted imaging (DWI) data. NF1 Patients were recruited from a phase II c...

Deep learning-assisted comparative analysis of animal trajectories with DeepHL.

Nature communications
A comparative analysis of animal behavior (e.g., male vs. female groups) has been widely used to elucidate behavior specific to one group since pre-Darwinian times. However, big data generated by new sensing technologies, e.g., GPS, makes it difficul...

pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep learning enables tremendous progress in medical image analysis. One driving force of this progress are open-source frameworks like TensorFlow and PyTorch. However, these frameworks rarely address issues specific to the ...

N2NSR-OCT: Simultaneous denoising and super-resolution in optical coherence tomography images using semisupervised deep learning.

Journal of biophotonics
Optical coherence tomography (OCT) imaging shows a significant potential in clinical routines due to its noninvasive property. However, the quality of OCT images is generally limited by inherent speckle noise of OCT imaging and low sampling rate. To ...