AIMC Topic: Image Processing, Computer-Assisted

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Development of a deep learning algorithm for Paneth cell density quantification for inflammatory bowel disease.

EBioMedicine
BACKGROUND: Alterations in ileal Paneth cell (PC) density have been described in gut inflammatory diseases such as Crohn's disease (CD) and could be used as a biomarker for disease prognosis. However, quantifying PCs is time-intensive, a barrier for ...

Reduction of Vision-Based Models for Fall Detection.

Sensors (Basel, Switzerland)
Due to the limitations that falls have on humans, early detection of these becomes essential to avoid further damage. In many applications, various technologies are used to acquire accurate information from individuals such as wearable sensors, envir...

Automatic face detection based on bidirectional recurrent neural network optimized by improved Ebola optimization search algorithm.

Scientific reports
Face detection is a multidisciplinary research subject that employs fundamental computer algorithms, image processing, and patterning. Neural networks, on the other hand, have been widely developed to solve challenges in the domains of feature extrac...

Learning to predict perceptual visibility of rendering deterioration in computer games.

Scientific reports
Contemporary computer gaming affords players the agency to manually tailor rendering settings, a capability crucial for optimizing computational demands following their hardware performance. Specifically, adjustments to texture resolution, shadow map...

Deep learning enables the use of ultra-high-density array in DNBSEQ.

Scientific reports
DNBSEQ employs a patterned array to facilitate massively parallel sequencing of DNA nanoballs (DNBs), leading to a considerable boost in throughput. By employing the ultra-high-density (UHD) array with an increased density of DNB binding sites, the t...

Brain tumor diagnosis in MRI scans images using Residual/Shuffle Network optimized by augmented Falcon Finch optimization.

Scientific reports
Brain tumor diagnosis is an important task in prognosing and treatment planning of the patients with brain cancer. in the meantime, using the Magnetic Resonance Imaging (MRI) as a commonly used non-invasive imaging technique provide the experts a hel...

Improving arterial stiffness prediction with machine learning utilizing hemodynamics and biomechanical features derived from phase contrast magnetic resonance imaging.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Arterial stiffness has emerged as a prominent marker of risk for cardiovascular diseases. Few studies are interested in predicting symptomatic or asymptomatic arterial stiffness from hemodynamics and biomechanics parameters. Machine learning models c...

Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images.

Sensors (Basel, Switzerland)
Skin cancer is the most common type of cancer in the United States and is estimated to affect one in five Americans. Recent advances have demonstrated strong performance on skin cancer detection, as exemplified by state of the art performance in the ...

Facial Image expression recognition and prediction system.

Scientific reports
Facial expression recognition system is an advanced technology that allows machines to recognize human emotions based on their facial expressions. In order to develop a robust prediction model, this research work proposes three distinct architectural...