AIMC Topic: Deep Learning

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Shallow and deep learning classifiers in medical image analysis.

European radiology experimental
An increasingly strong connection between artificial intelligence and medicine has enabled the development of predictive models capable of supporting physicians' decision-making. Artificial intelligence encompasses much more than machine learning, wh...

DDParcel: Deep Learning Anatomical Brain Parcellation From Diffusion MRI.

IEEE transactions on medical imaging
Parcellation of anatomically segregated cortical and subcortical brain regions is required in diffusion MRI (dMRI) analysis for region-specific quantification and better anatomical specificity of tractography. Most current dMRI parcellation approache...

SegX-Net: A novel image segmentation approach for contrail detection using deep learning.

PloS one
Contrails are line-shaped clouds formed in the exhaust of aircraft engines that significantly contribute to global warming. This paper confidently proposes integrating advanced image segmentation techniques to identify and monitor aircraft contrails ...

Calculation of solvation force in molecular dynamics simulation by deep-learning method.

Biophysical journal
Electrostatic calculations are generally used in studying the thermodynamics and kinetics of biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann equation on a large grid system, a process known to be time consuming....

An Intelligent Early Warning System for Harmful Algal Blooms: Harnessing the Power of Big Data and Deep Learning.

Environmental science & technology
Harmful algal blooms (HABs) pose a significant ecological threat and economic detriment to freshwater environments. In order to develop an intelligent early warning system for HABs, big data and deep learning models were harnessed in this study. Data...

Optimizing Coronary Computed Tomography Angiography Using a Novel Deep Learning-Based Algorithm.

Journal of imaging informatics in medicine
Coronary computed tomography angiography (CCTA) is an essential part of the diagnosis of chronic coronary syndrome (CCS) in patients with low-to-intermediate pre-test probability. The minimum technical requirement is 64-row multidetector CT (64-MDCT)...

From CNN to Transformer: A Review of Medical Image Segmentation Models.

Journal of imaging informatics in medicine
Medical image segmentation is an important step in medical image analysis, especially as a crucial prerequisite for efficient disease diagnosis and treatment. The use of deep learning for image segmentation has become a prevalent trend. The widely ad...

Systematic Review of Retinal Blood Vessels Segmentation Based on AI-driven Technique.

Journal of imaging informatics in medicine
Image segmentation is a crucial task in computer vision and image processing, with numerous segmentation algorithms being found in the literature. It has important applications in scene understanding, medical image analysis, robotic perception, video...

Pan-cancer image segmentation based on feature pyramids and Mask R-CNN framework.

Medical physics
BACKGROUND: Cancer, a disease with a high mortality rate, poses a great threat to patients' physical and mental health and can lead to huge medical costs and emotional damage. With the continuous development of artificial intelligence technologies, d...

Deep learning-assisted flavonoid-based fluorescent sensor array for the nondestructive detection of meat freshness.

Food chemistry
Gas sensors containing indicators have been widely used in meat freshness testing. However, concerns about the toxicity of indicators have prevented their commercialization. Here, we prepared three fluorescent sensors by complexing each flavonoid (fi...