AIMC Topic: Image Processing, Computer-Assisted

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UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients.

BMC medical imaging
BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international researchers. Recently, many deep learning-based Computed Tomography (CT) image/X-ray image fast screening mo...

Image Processing Technology in Remote Monitoring and Intelligent Medical System.

Journal of healthcare engineering
In order to study the application of image processing technology in remote monitoring and intelligent medical systems, the principle and implementation method of a remote intelligent image monitoring system based on virtual local area network is prop...

Electric Shovel Teeth Missing Detection Method Based on Deep Learning.

Computational intelligence and neuroscience
Electric shovels are widely used in the mining industry to dig ore, and the teeth in shovels' bucket can be lost due to the tremendous pressure exerted by ore materials during operation. When the teeth fall off and enter the crusher with other ore ma...

Macroeconomic Image Analysis and GDP Prediction Based on the Genetic Algorithm Radial Basis Function Neural Network (RBFNN-GA).

Computational intelligence and neuroscience
The prediction of gross domestic product (GDP) is a research hotspot, and its importance is self-evident. Its complex internal change mechanism also increases the difficulty of analyzing GDP data. The genetic algorithm (GA) is applied to the paramete...

Classification of renal biopsy direct immunofluorescence image using multiple attention convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Direct immunofluorescence (DIF) is an important medical evaluation tool for renal pathology. In the DIF images, the deposition appearances and locations of immunoglobulin on glomeruli involve immunological characteristics o...

Deep generative neural networks for spectral image processing.

Analytica chimica acta
An artificial intelligence approach based on deep generative neural networks for spectral imaging processing was proposed. The key idea was to treat different spectral image processing operations such as segmentation, regression, and classification a...

Cervical cell multi-classification algorithm using global context information and attention mechanism.

Tissue & cell
Cervical cancer is the second biggest killer of female cancer, second only to breast cancer. The cure rate of precancerous lesions found early is relatively high. Therefore, cervical cell classification has very important clinical value in the early ...

The Role of Machine Learning in Cardiovascular Pathology.

The Canadian journal of cardiology
Machine learning has seen slow but steady uptake in diagnostic pathology over the past decade to assess digital whole-slide images. Machine learning tools have incredible potential to standardise, and likely even improve, histopathologic diagnoses, b...

Random Fourier Features-Based Deep Learning Improvement with Class Activation Interpretability for Nerve Structure Segmentation.

Sensors (Basel, Switzerland)
Peripheral nerve blocking (PNB) is a standard procedure to support regional anesthesia. Still, correct localization of the nerve's structure is needed to avoid adverse effects; thereby, ultrasound images are used as an aid approach. In addition, imag...

A Hierarchical Feature Extraction Network for Fast Scene Segmentation.

Sensors (Basel, Switzerland)
Semantic segmentation is one of the most active research topics in computer vision with the goal to assign dense semantic labels for all pixels in a given image. In this paper, we introduce HFEN (Hierarchical Feature Extraction Network), a lightweigh...