AIMC Topic: Deep Learning

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Deep Learning-Based Segmentation of Morphologically Distinct Rat Hippocampal Reactive Astrocytes After Trimethyltin Exposure.

Toxicologic pathology
As regulators of homeostasis, astrocytes undergo morphological changes after injury to limit the insult in central nervous system (CNS). Trimethyltin (TMT) is a known neurotoxicant that induces reactive astrogliosis in rat CNS. To evaluate the degree...

Optimal Facial Feature Based Emotional Recognition Using Deep Learning Algorithm.

Computational intelligence and neuroscience
Humans have traditionally found it simple to identify emotions from facial expressions, but it is far more difficult for a computer system to do the same. The social signal processing subfield of emotion recognition from facial expression is used in ...

The Fusion Application of Deep Learning Biological Image Visualization Technology and Human-Computer Interaction Intelligent Robot in Dance Movements.

Computational intelligence and neuroscience
The paper aims to apply the deep learning-based image visualization technology to extract, recognize, and analyze human skeleton movements and evaluate the effect of the deep learning-based human-computer interaction (HCI) system. Dance education is ...

Style Transfer of Chinese Art Works Based on Dual Channel Deep Learning Model.

Computational intelligence and neuroscience
Aiming at the problems of style loss and lack of content in the style transfer of Chinese art works, this paper puts forward the style transfer technology of Chinese art works based on the dual channel deep learning model. On the basis of clarifying ...

Label-free intraoperative histology of bone tissue via deep-learning-assisted ultraviolet photoacoustic microscopy.

Nature biomedical engineering
Obtaining frozen sections of bone tissue for intraoperative examination is challenging. To identify the bony edge of resection, orthopaedic oncologists therefore rely on pre-operative X-ray computed tomography or magnetic resonance imaging. However, ...

Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers' performance and final diagnosis.

Japanese journal of radiology
PURPOSE: To evaluate the performance of a deep learning-based computer-aided detection (CAD) software for detecting pulmonary nodules, masses, and consolidation on chest radiographs (CRs) and to examine the effect of readers' experience and data char...

Improved Harris Hawks Optimization with Hybrid Deep Learning Based Heating and Cooling Load Prediction on residential buildings.

Chemosphere
In digital era, energy efficient building remains a hot research topic because of increasing concern regarding their environmental impact and energy consumption. Designing a suitable energy efficient building based on their layout namely overall area...

DeepBackRib: Deep learning to understand factors associated with readmissions after rib fractures.

The journal of trauma and acute care surgery
BACKGROUND: Deep neural networks yield high predictive performance, yet obscure interpretability limits clinical applicability. We aimed to build an explainable deep neural network that elucidates factors associated with readmissions after rib fractu...

Automatic identification of meibomian gland dysfunction with meibography images using deep learning.

International ophthalmology
BACKGROUND: Artificial intelligence is developing rapidly, bringing increasing numbers of intelligent products into daily life. However, it has little progress in dry eye, which is a common disease and associated with meibomian gland dysfunction (MGD...

Technical note: Rapid and high-resolution deep learning-based radiopharmaceutical imaging with 3D-CZT Compton camera and sparse projection data.

Medical physics
BACKGROUND: The Compton camera (CC) has great potential in nuclear medicine imaging due to the high detection efficiency and the ability to simultaneously detect multi-energy radioactive sources. However, the finite resolution of the detectors will d...