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Fig. 1. The overall framework of our multi-teacher distillation method.
Adaptive Multi-Teacher Knowledge Distillation for Segmentation
Medical image segmentation is a cornerstone of modern diagnostics, enabling precise identification of tumors, organs, and anomalies in MRI and CT scans....
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The flowchart of the medical image classification with SAM-based Image Enhancement (SAM-IE). The terms ‘low-grade’ and ‘high-grade’ can refer to benign and malignant, respectively, or to different degrees of disease severity.
SAM-IE: Enhancing Medical Imaging for Disease Detection
Medical imaging is a cornerstone of modern diagnostics, yet clinicians often grapple with challenges like ambiguous anatomical structures, inconsistent...
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Block diagram of the proposed Res-WG-KNN model for pneumonia prediction comprising two sub-models, and soft voting ensemble learning. RFC represents Regularized Fully Connected Layers, FV represents Feature Vector, and D represents Dimension. Pneumonia and Non-Pneumonia represented by subscripts p and n respectively.
AI MODEL Boosts Pneumonia Detection in Chest X-Rays
Pneumonia remains a leading cause of global mortality, particularly among children and the elderly. Early detection is critical for improving survival...
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10 Best Practices for Improving Website SEO
10 Best Practices for Improving Website SEO in 2025
Search engine optimization (SEO) is the backbone of digital success. In 2025, SEO strategies continue to evolve, making it crucial for website owners,...
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Fig. 8. The training process of the classification and grading of cardiac views.
CACTUS Framework: Revolutionizing Cardiac Care with Deep Transfer Learning in Ultrasound Imaging
Cardiovascular diseases remain the leading cause of death globally, underscoring the critical need for accurate and accessible diagnostic tools. Cardiac...
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complete overview of our proposed model for brain tunor classification
Revolutionizing Brain Tumor Classification: The Power of DEF-SwinE2NET
Brain tumors are among the most challenging medical conditions to diagnose and treat. Their complexity, coupled with the need for precise classification,...
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Generative Adversarial Networks (GAN)
Unveiling the Power of Generative Adversarial Networks (GANs): A Comprehensive Guide
In today’s rapidly evolving world of artificial intelligence and machine learning, one technology stands out for its innovative approach to data generation...
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A biopsy image of a complex wound analsis by AI, showing segmented tissue types like epidermis, dermis, and necrosis.
Revolutionizing Wound Care: How AI is Transforming Complex Wound Analysis
Chronic wounds affect millions of people worldwide, causing pain, disability, and staggering healthcare costs. According to the Wound Healing Society,...
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Diagram illustrating the overall study design and proposed Vision Transformer (ViT) framework for Keratitis Diagnosis using broad-beam, slit-beam, and blue-light anterior segment images.
Revolutionizing Keratitis Diagnosis: How Vision Transformers Are Transforming Eye Care
Infectious keratitis, a leading cause of corneal blindness, poses significant challenges for patients and healthcare providers. Misdiagnosis or delayed...
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Fig. 1. The overall framework of our multi-teacher distillation method.
Adaptive Multi-Teacher Knowledge Distillation for Segmentation
Medical image segmentation is a cornerstone of modern diagnostics, enabling precise identification of tumors, organs, and anomalies in MRI and CT scans. However, challenges like limited data, privacy concerns, and the computational complexity of deep...
The flowchart of the medical image classification with SAM-based Image Enhancement (SAM-IE). The terms ‘low-grade’ and ‘high-grade’ can refer to benign and malignant, respectively, or to different degrees of disease severity.
SAM-IE: Enhancing Medical Imaging for Disease Detection
Medical imaging is a cornerstone of modern diagnostics, yet clinicians often grapple with challenges like ambiguous anatomical structures, inconsistent image quality, and the sheer complexity of interpreting subtle pathological patterns. Traditional methods...
Block diagram of the proposed Res-WG-KNN model for pneumonia prediction comprising two sub-models, and soft voting ensemble learning. RFC represents Regularized Fully Connected Layers, FV represents Feature Vector, and D represents Dimension. Pneumonia and Non-Pneumonia represented by subscripts p and n respectively.
AI MODEL Boosts Pneumonia Detection in Chest X-Rays
Pneumonia remains a leading cause of global mortality, particularly among children and the elderly. Early detection is critical for improving survival rates, but traditional diagnostic methods rely heavily on chest X-rays (CXRs), which can be subjective...
10 Best Practices for Improving Website SEO
10 Best Practices for Improving Website SEO in 2025
Search engine optimization (SEO) is the backbone of digital success. In 2025, SEO strategies continue to evolve, making it crucial for website owners, marketers, and bloggers to stay updated. With search engines prioritizing user experience, content relevance,...
Fig. 8. The training process of the classification and grading of cardiac views.
CACTUS Framework: Revolutionizing Cardiac Care with Deep Transfer Learning in Ultrasound Imaging
Cardiovascular diseases remain the leading cause of death globally, underscoring the critical need for accurate and accessible diagnostic tools. Cardiac ultrasound, or echocardiography, is a cornerstone of heart disease assessment, offering real-time...

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