Kidney disease affects millions worldwide which emphasizes the need for early detection.
Recent advancements in deep learning have transformed medical diagnostics and provide …

In the era of digitalization, the biomedical sector has been affected by the spread of artificial
intelligence. In recent years, the possibility of using deep and machine learning methods for …

U-Net has demonstrated strong performance in the field of medical image segmentation and
has been adapted into various variants to cater to a wide range of applications. However …

Automated evaluation of all glomeruli throughout the whole kidney is essential for the
comprehensive study of kidney function as well as understanding the mechanisms of kidney …

Deep neural networks have shown excellent performance in medical image segmentation,
especially for cardiac images. Transformer-based models, though having advantages over …

Glomeruli are essential kidney structures for blood filtration. Their damage can impact the
filtering capability of the kidney, leading to its failure. Hence, glomerulus detection and …

Accurate segmentation and classification of glomeruli are fundamental to histopathology
slide analysis in renal pathology, which helps to characterize individual kidney disease …

Objective Recognizing glomerular lesions is essential in diagnosing chronic kidney disease.
However, deep learning faces challenges due to the lesion heterogeneity, superposition …

Glomerulus detection is a critical component of renal histopathology assessment, essential
for diagnosing glomerulonephritis. To mitigate the increasing workload on pathologists, AI …

Kidney diseases, especially those that affect the glomeruli, have become more common
worldwide in recent years. Accurate and early detection of glomeruli is critical for accurately …