Detecting mitosis from cell population is a fundamental problem in many biological
researches and biomedical applications. In modern researches, advanced imaging …

In this paper, we propose a straightforward and effective method for mitotic event detection
in time-lapse phase contrast microscopy image sequences of stem cell populations …

Mitosis, which has important effects such as healing and growing for human body, has
attracted considerable attention in recent years. Especially, cell division characteristics …

The amount of data handled by Internet of Medical Things (IoMT) devices grows
exponentially, which means higher exposure of sensitive data. The security and privacy of …

A variety of biological and pharmaceutical studies, such as for anti-cancer drugs, require the
quantification of cell responses over long periods of time. This is performed with time-lapse …

This paper proposes a nonnegative mix‐norm convex optimization method for mitotic cell
detection. First, we apply an imaging model‐based microscopy image segmentation method …

This paper proposes a clustered multi-task learning-based method for automated HEp-2
cells Classification. First, the visual feature is extracted for individual sample to represent its …

Due to the enormous potential and influence that stem cells may have in regenerative
medicine, there has been a rapidly growing interest in develo** tools to analyze and …

Accurate and automated identification of mitosis is essential and challenging to many
biomedical applications. To handle this challenge, we propose a novel mitotic cell …

Proposed is a sequential sparsity representation method for mitotic event recognition. First,
an imaging model‐based microscopy image segmentation method is implemented for …