In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …

Nucleus segmentation is an imperative step in the qualitative study of imaging datasets,
considered as an intricate task in histopathology image analysis. Segmenting a nucleus is …

Objective Cancer is the uncontrolled growth of abnormal cells that do not function as normal
cells. Lung cancer is the leading cause of cancer death in the world, so early detection of …

Purpose: Developing an artificial intelligence-based prostate cancer detection and
diagnosis system that can automatically determine important regions and accurately classify …

To minimize the damage caused by wildfires, a deep learning-based wildfire-detection
technology that extracts features and patterns from surveillance camera images was …

Deep Learning (DL) algorithms are a set of techniques that exploit large and/or complex real-
world datasets for cross-domain and cross-discipline prediction and classification tasks. DL …

Immunohistochemistry (IHC) is a diagnostic technique used throughout pathology. A
machine learning algorithm that could predict individual cell immunophenotype based on …

Mitotic cell detection is one of the challenging problems in the field of computational
pathology. Currently, mitotic cell detection and counting are one of the strongest prognostic …

Background The incidence of non-alcoholic fatty liver disease (NAFLD) and its progressive
form, non-alcoholic steatohepatitis (NASH), has been increasing for decades. Since the …

Multiplex immunofluorescence (mIF) assays multiple protein biomarkers on a single tissue
section. Recently, high-plex CODEX (co-detection by indexing) systems enable …