. Diabetic retinopathy (DR) is a serious diabetes complication that can lead to vision loss, making timely identification crucial. Existing data-driven algorithms for DR staging from digital fundus images (DFIs) often struggle with generalization due...
Computer methods and programs in biomedicine
Jan 21, 2025
BACKGROUND AND OBJECTIVE: Cloud-based Deep Learning as a Service (DLaaS) has transformed biomedicine by enabling healthcare systems to harness the power of deep learning for biomedical data analysis. However, privacy concerns emerge when sensitive us...
Journal of applied clinical medical physics
Jan 21, 2025
BACKGROUND: Accurate delineation of organs at risk (OARs) is crucial yet time-consuming in the radiotherapy treatment planning workflow. Modern artificial intelligence (AI) technologies had made automation of OAR contouring feasible. This report deta...
In image segmentation for medical image analysis, effective upsampling is crucial for recovering spatial information lost during downsampling. This challenge becomes more pronounced when dealing with diverse medical image modalities, which can signif...
The most deadly type of skin cancer is melanoma. A visual examination does not provide an accurate diagnosis of melanoma during its early to middle stages. Therefore, an automated model could be developed that assists with early skin cancer detection...
Biomedical physics & engineering express
Jan 21, 2025
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodo...
Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central ne...
Medical & biological engineering & computing
Jan 20, 2025
Source-free domain adaptation (SFDA) has become crucial in medical image analysis, enabling the adaptation of source models across diverse datasets without labeled target domain images. Self-training, a popular SFDA approach, iteratively refines self...
BACKGROUND: Food image recognition, a crucial step in computational gastronomy, has diverse applications across nutritional platforms. Convolutional neural networks (CNNs) are widely used for this task due to their ability to capture hierarchical fea...
In response to the increasing prevalence of dental diseases, dental health, a vital aspect of human well-being, warrants greater attention. Panoramic X-ray images (PXI) and Cone Beam Computed Tomography (CBCT) are key tools for dentists in diagnosing...
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