AIMC Topic: Image Processing, Computer-Assisted
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EFCNet enhances the efficiency of segmenting clinically significant small medical objects.
Scientific reports
Apr 14, 2025
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...
Comparison of artificial intelligence applications and commercial system performances using selected ANA IIF images.
Immunologic research
Apr 14, 2025
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...
Depth-of-interaction encoding techniques for pixelated PET detectors enabled by machine learning methods and fast waveform digitization.
Physics in medicine and biology
Apr 14, 2025
. 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...
A dual-branch hybrid network with bilateral-difference awareness for collateral scoring on CT angiography of acute ischemic stroke patients.
Physics in medicine and biology
Apr 14, 2025
Acute ischemic stroke (AIS) patients with good collaterals tend to have better outcomes after endovascular therapy. Existing collateral scoring methods rely mainly on vessel segmentation and convolutional neural networks (CNNs), often ignoring bilate...
Uncertainty-aware segmentation quality prediction via deep learning Bayesian Modeling: Comprehensive evaluation and interpretation on skin cancer and liver segmentation.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 13, 2025
Image segmentation is a critical step in computational biomedical image analysis, typically evaluated using metrics like the Dice coefficient during training and validation. However, in clinical settings without manual annotations, assessing segmenta...
Explainable AI for lung cancer detection via a custom CNN on CT images.
Scientific reports
Apr 13, 2025
Lung cancer, which claims 1.8 million lives annually, is still one of the leading causes of cancer-related deaths globally. Patients with lung cancer frequently have a bad prognosis because of late-stage detection, which severely limits treatment opt...
Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images.
Scientific reports
Apr 13, 2025
In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with a convolutional neural network (CNN) model designed to classify four stages of Alzheimer's disease (AD): Mild Dementia (MD), Moderate Dementia (M...
HALSR-Net: Improving CNN Segmentation of Cardiac Left Ventricle MRI with Hybrid Attention and Latent Space Reconstruction.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 12, 2025
Accurate cardiac MRI segmentation is vital for detailed cardiac analysis, yet the manual process is labor-intensive and prone to variability. Despite advancements in MRI technology, there remains a significant need for automated methods that can reli...
Stable distance regression via spatial-frequency state space model for robot-assisted endomicroscopy.
International journal of computer assisted radiology and surgery
Apr 12, 2025
PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) is a noninvasive technique that enables the direct visualization of tissue at a microscopic level in real time. One of the main challenges in using pCLE is maintaining the probe within a worki...
Novel CT radiomics models for the postoperative prediction of early recurrence of resectable pancreatic adenocarcinoma: A single-center retrospective study in China.
Journal of applied clinical medical physics
Apr 11, 2025
PURPOSE: To assess the predictive capability of CT radiomics features for early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC).
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