Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …

In modern clinical practice, digital pathology has an essential role, being a technological
necessity for the activity in the pathological anatomy laboratories. The development of …

Artificial intelligence methods including deep neural networks (DNN) can provide rapid
molecular classification of tumors from routine histology with accuracy that matches or …

Background Histological assessment of colorectal cancer (CRC) tissue is a crucial and
demanding task for pathologists. Unfortunately, manual annotation by trained specialists is a …

The advent of whole slide imaging has brought advanced computer-aided diagnosis via
medical imaging and artificial intelligence technologies in digital pathology. The …

Microscopic analyses of tissue samples are crucial for confirming the diagnosis of breast
cancer. The digitization of these samples has led to the development of computational …

Hematoxylin and Eosin (H&E) staining is a widely used sample preparation procedure for
enhancing the saturation of tissue sections and the contrast between nuclei and cytoplasm …

Image synthesis techniques have limited application in the medical field due to
unsatisfactory authenticity and precision. Additionally, synthesizing diverse outputs is …

The use of digitized data in pathology research is rapidly increasing. The whole slide image
(WSI) is an indispensable part of the visual examination of slides in digital pathology and …

In the present study, we propose a novel case-based similar image retrieval (SIR) method
for hematoxylin and eosin (H&E) stained histopathological images of malignant lymphoma …