Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …

Objective Development of novel informatics methods focused on improving pregnancy
outcomes remains an active area of research. The purpose of this study is to systematically …

Abstract Background and Objective: Deep learning techniques are powerful tools for image
analysis. However, the lack of programming experience makes it difficult for novice users to …

Objective: Nucleus recognition is a critical yet challenging step in histopathology image
analysis, for example, in Ki67 immunohistochemistry stained images. Although many …

Prevention of infectious diseases, diagnosis of diseases, and determination of treatment
options all rely on biosensors to detect and analyze biomarkers, which are usually divided …

In this paper, a novel bacterial foraging algorithm (BFA)-Gaussian support vector classifier
machine (GSVCM) model was proposed to improve the fatigue classification accuracy of …

In-vitro fertilization (IVF), as the most common fertility treatment, has never reached its
maximum potentials. Systematic selection of embryos with the highest implementation …

Red blood cell counts have been proven to be one of the most frequently performed blood
tests and are valuable for early diagnosis of some diseases. This paper describes an …

Recent innovations in tissue clearing and light-sheet microscopy allow the rapid acquisition
of intact micron-resolution images in fluorescently labeled samples. Automated, accurate …

Cell nucleus segmentation remains an open and challenging problem especially to segment
nuclei in cell clumps. Splitting a cell clump would be straightforward if the gradients of …