AIMC Topic: Deep Learning

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Deep learning based real-time tourist spots detection and recognition mechanism.

Science progress
More and more information on tourist spots is being represented as pictures rather than text. Consequently, tourists who are interested in a specific attraction shown in pictures may have no idea how to perform a text search to get more information a...

[Early Assessment of Myocardial Fibrosis of Hypertrophic Cardiomyopathy with Native-T1-Mapping-Based Deep Learning: A Preliminary Study].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To explore the diagnostic performance of deep learning (DL) model in early detection of the interstitial myocardial fibrosis using native T1 maps of hypertrophic cardiomyopathy (HCM) without late gadolinium enhancement (LGE).

[Application of Deep Learning Reconstruction Algorithm in Low-Dose Thin-Slice Liver CT of Healthy Volunteers].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To explore the clinical feasibility of applying deep learning (DL) reconstruction algorithm in low-dose thin-slice liver CT examination of healthy volunteers by comparing the reconstruction algorithm based on DL, filtered back projection (...

Deep learning and capsule endoscopy: automatic identification and differentiation of small bowel lesions with distinct haemorrhagic potential using a convolutional neural network.

BMJ open gastroenterology
OBJECTIVE: Capsule endoscopy (CE) is pivotal for evaluation of small bowel disease. Obscure gastrointestinal bleeding most often originates from the small bowel. CE frequently identifies a wide range of lesions with different bleeding potentials in t...

A Deep Learning System for Automatic Assessment of Anterior Chamber Angle in Ultrasound Biomicroscopy Images.

Translational vision science & technology
PURPOSE: To develop and assess a deep learning system that automatically detects angle closure and quantitatively measures angle parameters from ultrasound biomicroscopy (UBM) images using a deep learning algorithm.

Training for object recognition with increasing spatial frequency: A comparison of deep learning with human vision.

Journal of vision
The ontogenetic development of human vision and the real-time neural processing of visual input exhibit a striking similarity-a sensitivity toward spatial frequencies that progresses in a coarse-to-fine manner. During early human development, sensiti...

Deep-Learning-Based Pre-Diagnosis Assessment Module for Retinal Photographs: A Multicenter Study.

Translational vision science & technology
PURPOSE: Artificial intelligence (AI) deep learning (DL) has been shown to have significant potential for eye disease detection and screening on retinal photographs in different clinical settings, particular in primary care. However, an automated pre...

Which deep learning model can best explain object representations of within-category exemplars?

Journal of vision
Deep neural network (DNN) models realize human-equivalent performance in tasks such as object recognition. Recent developments in the field have enabled testing the hierarchical similarity of object representation between the human brain and DNNs. Ho...

Perception and memory in the medial temporal lobe: Deep learning offers a new lens on an old debate.

Neuron
In this issue of Neuron, Bonnen et al. (2021) use artificial neural networks to resolve a long-standing controversy surrounding the neurocognitive dichotomy between memory and perception. They show that the perirhinal cortex supports performance on t...

Detection of Optic Disc Abnormalities in Color Fundus Photographs Using Deep Learning.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: To date, deep learning-based detection of optic disc abnormalities in color fundus photographs has mostly been limited to the field of glaucoma. However, many life-threatening systemic and neurological conditions can manifest as optic dis...