The second decade of the twenty-first century witnessed a new challenge in the handling of
microscopy data. Big data, data deluge, large data, data compliance, data analytics, data …

Accurately counting the number of cells in microscopy images is required in many medical
diagnosis and biological studies. This task is tedious, time-consuming, and prone to …

Artificial neural networks (ANNs) are one of the primary types of artificial intelligence and
have been rapidly developed and used in many fields. In recent years, there has been a …

Cell counting plays a vital role in biomedical researches. However, manual cell counting is
time‐consuming, laborious, and low efficiency and has a high counting error rate problem …

Microalgae photobioreactors integrated into double-skin façades in cold climates enhance
growth conditions for biomass generation, CO 2 fixation, and O 2 production, while reducing …

To facilitate rapid determination of cellular viability caused by the inhibitory effect of drugs,
numerical deep learning algorithms was used for unlabeled cell culture images captured by …

Counting microscopic cells is a time-consuming task and exhausting, but it is important to
assess the different experimental conditions and effects on biological structures of interest …

The investigation of biological systems with three-dimensional microscopy demands
automatic cell identification methods that not only are accurate but also can imply the …

Counting the number of Circulating Tumor Cells (CTCs) for cancer screenings is currently
done by cytopathologists with a heavy time and energy cost. AI, especially deep learning …

Cell detection and segmentation are integral parts of automated systems in digital
pathology. Encoder-decoder networks have emerged as a promising solution for these …