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Introduction of Medical Imaging Modalities
The diagnosis and treatment of various diseases had been expedited with the help of medical imaging. Different medical imaging modalities, including...
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Introduction to Medical Imaging Informatics
Medical imaging informatics is a rapidly growing field that combines the principles of medical imaging and informatics to improve the acquisition,...
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Automl Systems for Medical Imaging
The integration of machine learning in medical image analysis can greatly enhance the quality of healthcare provided by physicians. The combination...
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Model Fooling Threats Against Medical Imaging
Automatic medical image diagnosis tools are vulnerable to modern model fooling technologies. Because medical imaging is a way of determining the...
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Invariant Scattering Transform for Medical Imaging
Over the years, the Invariant Scattering Transform (IST) technique has become popular for medical image analysis, including using wavelet transform...
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How Generative AI Is Transforming Medical Imaging: A Practical Guide
Medical imaging is a crucial aspect of modern healthcare, as it enables the diagnosis and treatment of various diseases and conditions. However,...
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Advancing Medical Imaging Through Generative Adversarial Networks: A Comprehensive Review and Future Prospects
In medical imaging, traditional methods have long been relied upon. However, the integration of Generative Adversarial Networks (GANs) has sparked a...
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Web-Based AI System for Medical Image Segmentation
Image segmentation is a crucial step in the diagnosis of brain tumours, and machine learning has emerged as a promising tool for tumour...
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From single to universal: tiny lesion detection in medical imaging
Accurate and automatic detection of tiny lesions in medical imaging plays a critical role in comprehensive cancer diagnosis, staging, treatment,...
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Radiological Medical Imaging Annotation and Visualization Tool
Significant medical image visualization and annotation tools, tailored for clinical users, play a crucial role in disease diagnosis and treatment....
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Harbor seal whiskers optimization algorithm with deep learning-based medical imaging analysis for gastrointestinal cancer detection
Gastrointestinal (GI) cancer detection includes the detection of cancerous or potentially cancerous lesions within the GI tract. Earlier diagnosis is...
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Recent trend in medical imaging modalities and their applications in disease diagnosis: a review
Medical Imaging (MI) plays a crucial role in healthcare, including disease diagnosis, treatment, and continuous monitoring. The integration of...
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Deep anonymization of medical imaging
Deep learning has shown record-shattering performance in multiple medical tasks. However, data quantity and quality are crucial requirements. As a...
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Optifusion: advancing visual intelligence in medical imaging through optimized CNN-TQWT fusion
The domain of medical image fusion has garnered considerable attention within the biomedical imaging and clinical analysis communities. Despite the...
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Appearance-based Debiasing of Deep Learning Models in Medical Imaging
Out-of-distribution data can substantially impede the performance of deep learning models. In medical imaging, domain shifts can, for instance, be...
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Semi-supervised medical imaging segmentation with soft pseudo-label fusion
Segmentation is an essential task in modern medical imaging analysis. Since the scarcity of labeled pixel-level annotations often limits its wide...
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Bias, Ethical concerns, and explainable decision-making in medical imaging research
Medical imaging research has the potential to improve patient outcomes by enabling earlier detection, more accurate diagnosis, and more targeted...
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Training Methods of Innovative Talents in Medical Imaging Informatics Under the Background of New Engineering
It is crucial to cultivate the innovative ability of graduate students under the background of new engineering. In this article, we recommend...
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Exploring Optimal Configurations in Active Learning for Medical Imaging
Medical imaging is a critical component of clinical decision-making, patient diagnosis, treatment planning, intervention, and therapy. However, due...
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Designing User-Centric Explanations for Medical Imaging with Informed Machine Learning
A flawed algorithm released in clinical practice can cause unintended harm to patient health. Risks, regulation, responsibility, and ethics shape the...