In order to extract more important morphological features of neuron images and achieve accurate classification of the neuron type, a method is proposed that uses Sugeno fuzzy integral integration of three optimized deep learning models, namely AlexNe...
Crop diseases can significantly affect various aspects of crop cultivation, including crop yield, quality, production costs, and crop loss. The utilization of modern technologies such as image analysis via machine learning techniques enables early an...
Landmark detection is a crucial task in medical image analysis, with applications across various fields. However, current methods struggle to accurately locate landmarks in medical images with blurred tissue boundaries due to low image quality. In pa...
International journal of neural systems
Jul 10, 2024
The quality of medical images is crucial for accurately diagnosing and treating various diseases. However, current automated methods for assessing image quality are based on neural networks, which often focus solely on pixel distortion and overlook t...
Brain atrophy measurements derived from magnetic resonance imaging (MRI) are a promising marker for the diagnosis and prognosis of neurodegenerative pathologies such as Alzheimer's disease or multiple sclerosis. However, its use in individualized ass...
Whole slide imaging (WSI) of pathology glass slides using high-resolution scanners has enabled the large-scale application of artificial intelligence (AI) in pathology, to support the detection and diagnosis of disease, potentially increasing efficie...
BACKGROUND: As an important part of the tongue, the tongue coating is closely associated with different disorders and has major diagnostic benefits. This study aims to construct a neural network model that can perform complex tongue coating segmentat...
Cytomegalovirus retinitis (CMVR) is a significant cause of vision loss. Regular screening is crucial but challenging in resource-limited settings. A convolutional neural network is a state-of-the-art deep learning technique to generate automatic diag...
SIGNIFICANCE: Imaging blood oxygen saturation ( ) in the skin can be of clinical value when studying ischemic tissue. Emerging multispectral snapshot cameras enable real-time imaging but are limited by slow analysis when using inverse Monte Carlo (M...
Journal of imaging informatics in medicine
Jul 9, 2024
Deep neural networks have shown excellent performance in medical image segmentation, especially for cardiac images. Transformer-based models, though having advantages over convolutional neural networks due to the ability of long-range dependence lear...
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