Digital pathology is on the verge of becoming a mainstream option for routine diagnostics.
Faster whole slide image scanning has paved the way for this development, but …

The emergence of digital pathology—an image-based environment for the acquisition,
management and interpretation of pathology information supported by computational …

Automatic medical image segmentation plays a critical role in scientific research and
medical care. Existing high-performance deep learning methods typically rely on large …

The application of deep learning for automated segmentation (delineation of boundaries) of
histologic primitives (structures) from whole slide images can facilitate the establishment of …

Background Nephropathologic analyses provide important outcomes-related data in
experiments with the animal models that are essential for understanding kidney disease …

Recently, due to the increasing requirements of medical imaging applications and the
professional requirements of annotating medical images, few-shot learning has gained …

Background Pathologists use visual classification of glomerular lesions to assess samples
from patients with diabetic nephropathy (DN). The results may vary among pathologists …

To improve the diagnosis of Lupus Nephritis (LN), a multilevel LN image segmentation
method is developed in this paper based on an improved slime mould algorithm. The search …

Background Transplant nephropathology is a highly specialized field of pathology
comprising both the evaluation of organ donor biopsy for organ allocation and post …

Context.—Recent developments in machine learning have stimulated intense interest in
software that may augment or replace human experts. Machine learning may impact …