Medical & biological engineering & computing
Apr 15, 2025
The aim of this study was to develop a deep learning method for analyzing CT images with varying doses and qualities, aiming to categorize lung lesions into nodules and non-nodules. This study utilized the lung nodule analysis 2016 challenge dataset....
Neural networks : the official journal of the International Neural Network Society
Apr 15, 2025
Multi-stage methods have been proven effective and widely used in image deblurring research. These methods, usually designed based on Convolutional Neural Networks (CNNs) or Vision Transformers (ViTs), have limitations, including the inability to cap...
PURPOSE: The aim of this study was to develop a saturation transfer MR fingerprinting (ST-MRF) technique using a biophysics model-driven deep learning approach.
Bacterial infections pose a significant biosafety concern, making early and accurate diagnosis essential for effective treatment and prognosis. Traditional diagnostic methods, while reliable, are often slow and fail to meet urgent clinical demands. I...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 14, 2025
BACKGROUND: The presence of a gap between adjacent detector blocks in Positron Emission Tomography (PET) scanners introduces a partial loss of projection data, which can degrade the image quality and quantitative accuracy of reconstructed PET images....
Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) ...
Diffusion tensor imaging (DTI) is essential for assessing brain microstructure but requires long acquisition times, limiting clinical use. Recent deep learning (DL) approaches, such as SuperDTI or deepDTI, improve DTI metrics but demand large, high-q...
Efficient segmentation of small hyperreflective dots, key biomarkers for diseases like macular edema, is critical for diagnosis and treatment monitoring.However, existing models, including Convolutional Neural Networks (CNNs) and Transformers, strugg...
Accurate and accessible classification of anti-nuclear antibodies (ANA) through indirect immunofluorescence (IIF) imaging is crucial for diagnosing autoimmune diseases. However, many laboratories, particularly those with limited resources, lack acces...
. Pixelated detectors with single-ended readout are routinely used by commercial positron emission tomography scanners owing to their good energy and timing resolution and optimized manufacturing, but they typically do not provide depth-of-interactio...
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