AIMC Topic: Diagnostic Imaging

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Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries.

Scientific reports Feb 15, 2023
Most artificial intelligence (AI) research and innovations have concentrated in high-income countries, where imaging data, IT infrastructures and clinical expertise are plentiful. However, slower progress has been made in limited-resource environment...
Artificial Intelligence Pregnancy Humans Diagnostic Imaging Egypt Female Deep Learning Malawi
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Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging.

Sensors (Basel, Switzerland) Feb 10, 2023
Personal identification using analysis of the internal and external characteristics of the human finger is currently an intensively developed topic. The work in this field concerns new methods of feature extraction and image analysis, mainly using mo...
Diagnostic Imaging Fingers Biometry Upper Extremity Humans Artificial Intelligence
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Efficient Evolving Deep Ensemble Medical Image Captioning Network.

IEEE journal of biomedical and health informatics Feb 3, 2023
With the advancement in artificial intelligence (AI) based E-healthcare applications, the role of automated diagnosis of various diseases has increased at a rapid rate. However, most of the existing diagnosis models provide results in a binary fashio...
Artificial Intelligence Image Processing, Computer-Assisted Humans Diagnostic Imaging
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Nearest Neighbor-Based Strategy to Optimize Multi-View Triplet Network for Classification of Small-Sample Medical Imaging Data.

IEEE transactions on neural networks and learning systems Feb 3, 2023
Multi-view classification with limited sample size and data augmentation is a very common machine learning (ML) problem in medicine. With limited data, a triplet network approach for two-stage representation learning has been proposed. However, effec...
Machine Learning Diagnostic Imaging Neural Networks, Computer
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Multiclass datasets expand neural network utility: an example on ankle radiographs.

International journal of computer assisted radiology and surgery Feb 2, 2023
PURPOSE: Artificial intelligence in computer vision has been increasingly adapted in clinical application since the implementation of neural networks, potentially providing incremental information beyond the mere detection of pathology. As its algori...
Artificial Intelligence Humans Fractures, Bone Neural Networks, Computer Ankle Radiography Diagnostic Imaging
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Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives.

Medical image analysis Jan 31, 2023
Transformer, one of the latest technological advances of deep learning, has gained prevalence in natural language processing or computer vision. Since medical imaging bear some resemblance to computer vision, it is natural to inquire about the status...
Humans Neural Networks, Computer Diagnostic Imaging
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Artificial Intelligence in Paediatric Tuberculosis.

Pediatric radiology Jan 28, 2023
Tuberculosis (TB) continues to be a leading cause of death in children despite global efforts focused on early diagnosis and interventions to limit the spread of the disease. This challenge has been made more complex in the context of the coronavirus...
Diagnostic Imaging Humans Tuberculosis Child Artificial Intelligence Radiography Diagnosis, Computer-Assisted
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Signal to noise ratio quantifies the contribution of spectral channels to classification of human head and neck tissues using deep learning and multispectral imaging.

Journal of biomedical optics Jan 28, 2023
SIGNIFICANCE: Accurate identification of tissues is critical for performing safe surgery. Combining multispectral imaging (MSI) with deep learning is a promising approach to increasing tissue discrimination and classification. Evaluating the contribu...
Neural Networks, Computer Humans Diagnostic Imaging Deep Learning Signal-To-Noise Ratio
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PlexusNet: A neural network architectural concept for medical image classification.

Computers in biology and medicine Jan 26, 2023
State-of-the-art (SOTA) convolutional neural network models have been widely adapted in medical imaging and applied to address different clinical problems. However, the complexity and scale of such models may not be justified in medical imaging and s...
Adaptation, Physiological Algorithms Neural Networks, Computer Diagnostic Imaging
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Using deep learning to detect diabetic retinopathy on handheld non-mydriatic retinal images acquired by field workers in community settings.

Scientific reports Jan 25, 2023
Diabetic retinopathy (DR) at risk of vision loss (referable DR) needs to be identified by retinal screening and referred to an ophthalmologist. Existing automated algorithms have mostly been developed from images acquired with high cost mydriatic ret...
Mydriatics Humans Diabetic Retinopathy Mass Screening Deep Learning Diagnostic Imaging Diabetes Mellitus Prospective Studies Retina Sensitivity and Specificity Photography
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