Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …

Breast cancer is the most common malignant disease in women worldwide. In recent
decades, earlier diagnosis and better adjuvant therapy have substantially improved patient …

Staining and scanning of tissue samples for microscopic examination is fraught with
undesirable color variations arising from differences in raw materials and manufacturing …

Morphometric analysis of nuclei is crucial in cytological examinations. Unfortunately, nuclei
segmentation presents many challenges because they usually create complex clusters in …

In kidney transplantations, the evaluation of the vascular structures and stromal areas is
crucial for determining kidney acceptance, which is currently based on the pathologist's …

Color variation in stained histopathology images prevents the development of computer-
assisted diagnosis (CAD) algorithms for whole slide imaging systems. Therefore, stain …

Analysis of morphometric features of nuclei plays an important role in understanding
disease progression and predict efficacy of treatment. First step towards this goal requires …

One of the foremost and challenging tasks in hematoxylin and eosin stained histological
image analysis is to reduce color variation present among images, which may significantly …

In the medical realm, the pivotal role of pathological Whole Slide Images (WSIs) in detecting
cancer, tracking disease progression, and evaluating treatment efficacy is indisputable …

Stain in-homogeneity adversely affects segmentation and quantification of tissues in
histology images. Stain normalisation techniques have been used to standardise the …