AIMC Topic: Diagnostic Imaging

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Superlative Feature Selection Based Image Classification Using Deep Learning in Medical Imaging.

Journal of healthcare engineering Sep 26, 2022
Medical image recognition plays an essential role in the forecasting and early identification of serious diseases in the field of identification. Medical pictures are essential to a patient's health record since they may be used to control, manage, a...
Humans Algorithms Deep Learning Radiography Diagnostic Imaging
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Artificial intelligence in adrenal imaging: A critical review of current applications.

Diagnostic and interventional imaging Sep 24, 2022
In the elective field of adrenal imaging, artificial intelligence (AI) can be used for adrenal lesion detection, characterization, hypersecreting syndrome management and patient follow-up. Although a perfect AI tool that includes all required steps f...
Humans Artificial Intelligence Machine Learning Algorithms Deep Learning Diagnostic Imaging
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Japan Ocular Imaging Registry: a national ophthalmology real-world database.

Japanese journal of ophthalmology Sep 23, 2022
In 2017, the Japanese Ophthalmological Society (JOS) created the Japan Ocular Imaging (JOI) registry, a national database of images and clinical data in the field of ophthalmology in Japan. The JOI registry automatically transfers the information sto...
Humans Artificial Intelligence Nigeria United States Multicenter Studies as Topic Diagnostic Imaging Ophthalmology Registries Japan
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Text-Guided Human Image Manipulation via Image-Text Shared Space.

IEEE transactions on pattern analysis and machine intelligence Sep 14, 2022
Text is a new way to guide human image manipulation. Albeit natural and flexible, text usually suffers from inaccuracy in spatial description, ambiguity in the description of appearance, and incompleteness. We in this paper address these issues. To o...
Humans Neural Networks, Computer Algorithms Diagnostic Imaging
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SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging.

IEEE journal of biomedical and health informatics Sep 9, 2022
Federated learning is an emerging research paradigm for enabling collaboratively training deep learning models without sharing patient data. However, the data from different institutions are usually heterogeneous across institutions, which may reduce...
Humans Neural Networks, Computer Deep Learning Radiography Diagnostic Imaging
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Artificial Intelligence in the Imaging of Diffuse Lung Disease.

Radiologic clinics of North America Sep 7, 2022
Diffuse lung diseases are a heterogeneous group of disorders that can be difficult to differentiate by imaging using traditional methods of evaluation. The overlap between various disorders results in difficulty when medical professionals attempt to ...
Humans Neural Networks, Computer Artificial Intelligence Diagnostic Imaging Lung Diseases
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Cardiovascular Imaging in China: Yesterday, Today, and Tomorrow.

Journal of thoracic imaging Sep 6, 2022
The high prevalence and mortality of cardiovascular diseases in China's large population has increased the use of cardiovascular imaging for the assessment of conditions in recent years. In this study, we review the past 20 years of cardiovascular im...
Humans Artificial Intelligence China Diagnostic Imaging
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Fast, efficient, and accurate neuro-imaging denoising via supervised deep learning.

Nature communications Sep 2, 2022
Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power. While deep-learning methods have recently been applie...
Animals Deep Learning Image Processing, Computer-Assisted Diagnostic Imaging Calcium Signal-To-Noise Ratio Caenorhabditis elegans
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Advances in Deep-Learning-Based Sensing, Imaging, and Video Processing.

Sensors (Basel, Switzerland) Aug 18, 2022
Deep learning techniques have shown their capabilities to discover knowledge from massive unstructured data, providing data-driven solutions for representation and decision making [...].
Deep Learning Diagnostic Imaging
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Comparison of Different Convolutional Neural Network Activation Functions and Methods for Building Ensembles for Small to Midsize Medical Data Sets.

Sensors (Basel, Switzerland) Aug 16, 2022
CNNs and other deep learners are now state-of-the-art in medical imaging research. However, the small sample size of many medical data sets dampens performance and results in overfitting. In some medical areas, it is simply too labor-intensive and ex...
Neural Networks, Computer Diagnostic Imaging
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