AIMC Topic: Algorithms

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Semi-Supervised Unpaired Medical Image Segmentation Through Task-Affinity Consistency.

IEEE transactions on medical imaging
Deep learning-based semi-supervised learning (SSL) algorithms are promising in reducing the cost of manual annotation of clinicians by using unlabelled data, when developing medical image segmentation tools. However, to date, most existing semi-super...

The Path Planning and Location Method of Inspection Robot in a Large Storage Tank Bottom.

Computational intelligence and neuroscience
With the development of robot technology, inspection robots have been applied to the defect detection of large tanks. However, the existing path planning algorithm of the tank bottom detection robot is easy to fall into the local minimum, and the pat...

A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation.

Computers in biology and medicine
Deep learning-based methods have become the dominant methodology in medical image processing with the advancement of deep learning in natural image classification, detection, and segmentation. Deep learning-based approaches have proven to be quite ef...

Deep learning based MRI reconstruction with transformer.

Computer methods and programs in biomedicine
Magnetic resonance imaging (MRI) has become one of the most powerful imaging techniques in medical diagnosis, yet the prolonged scanning time becomes a bottleneck for application. Reconstruction methods based on compress sensing (CS) have made progre...

A general framework for robust stability analysis of neural networks with discrete time delays.

Neural networks : the official journal of the International Neural Network Society
Robust stability of different types of dynamical neural network models including time delay parameters have been extensively studied, and many different sets of sufficient conditions ensuring robust stability of these types of dynamical neural networ...

Artificial Intelligence for Hip Fracture Detection and Outcome Prediction: A Systematic Review and Meta-analysis.

JAMA network open
IMPORTANCE: Artificial intelligence (AI) enables powerful models for establishment of clinical diagnostic and prognostic tools for hip fractures; however the performance and potential impact of these newly developed algorithms are currently unknown.

Myoelectric Pattern Recognition Using Gramian Angular Field and Convolutional Neural Networks for Muscle-Computer Interface.

Sensors (Basel, Switzerland)
In the field of the muscle-computer interface, the most challenging task is extracting patterns from complex surface electromyography (sEMG) signals to improve the performance of myoelectric pattern recognition. To address this problem, a two-stage a...

Automated Monkeypox Skin Lesion Detection Using Deep Learning and Transfer Learning Techniques.

International journal of environmental research and public health
The current outbreak of monkeypox (mpox) has become a major public health concern because of the quick spread of this disease across multiple countries. Early detection and diagnosis of mpox is crucial for effective treatment and management. Consider...

Edge computing on TPU for brain implant signal analysis.

Neural networks : the official journal of the International Neural Network Society
The ever-increasing number of recording sites of silicon-based probes imposes a great challenge for detecting and evaluating single-unit activities in an accurate and efficient manner. Currently separate solutions are available for high precision off...