Phase-contrast microscopy is one of the most common and convenient imaging modalities
to observe long-term multi-cellular processes, which generates images by the interference of …

Automatic cell segmentation can hardly be flawless due to the complexity of image data
particularly when time-lapse experiments last for a long time without biomarkers. To address …

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 …

Objective: The objective of this paper is to improve the visualization and detection of tissue
folds, which are prominent among tissue slides, from the pre-scan image of a whole slide …

Cell detection in microscopy images is essential for automated cell behavior analysis
including cell shape analysis and cell tracking. Robust cell detection in high-density and low …

Neuron segmentation in two-photon microscopy images is a critical step to investigate
neural network activities in vivo. However, it still remains as a challenging problem due to …

The restoration of microscopy images makes the segmentation and detection of cells easier
and more reliable, which facilitates automated cell tracking and cell behavior analysis. In this …

Differential interference contrast (DIC) microscopy is widely used for observing unstained
biological samples that are otherwise optically transparent. Combining this optical technique …

Cell image segmentation is an important step in medical image processing and analysis
system. The watershed algorithm is usually used to segment cells in the image. However, it …

Most of the erythrocyte related diseases are detectable by hematology images analysis. At
the first step of this analysis, segmentation and detection of blood cells are inevitable. In this …