Introduction Artificial intelligence (AI) integration in nephropathology has been growing
rapidly in recent years, facing several challenges including the wide range of histological …

The percent global glomerulosclerosis is a key factor in determining the outcome of renal
transfer surgery. At present, the rate is typically computed by pathologists, which is labour …

Accurate and quick binuclear cell (BC) detection plays a significant role in predicting the risk
of leukemia and other malignant tumors. However, manual counting of BCs using …

Background: Deep learning has great potential in digital kidney pathology. However, its
effectiveness depends heavily on the availability of extensively labeled datasets, which are …

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

Methods The Web of Science Core Collection was utilized to identify publications related to
the research or applications of CV technology in the field of kidney medicine from January 1 …

Purpose Generalization is one of the main challenges of computational pathology. Slide
preparation heterogeneity and the diversity of scanners lead to poor model performance …

Segmenting glomerular intraglomerular tissue and lesions traditionally depends on detailed
morphological evaluations by expert nephropathologists, a labor-intensive process …

When we proposed this Journal of Medical Imaging(JMI) Special Section around the
analysis of high-dimensional medical imaging data, we envisioned bringing together diverse …

Current deep learning models for classifying glomeruli in nephropathology are trained
almost exclusively in a supervised manner, requiring expert-labeled images. Very little is …