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 …

Single nucleus segmentation is a frequent challenge of microscopy image processing, since
it is the first step of many quantitative data analysis pipelines. The quality of tracking single …

In developmental biology, knowledge of cell structure and their (morpho) dynamic behavior,
leads to a comprehensive understanding of their conducts and the mechanisms in which …

Multiplexed fluorescence in situ hybridization techniques have enabled cell-type
identification, linking transcriptional heterogeneity with spatial heterogeneity of cells …

An important challenge in the cyber-space is the effective identification of network
anomalies, often caused by malicious activities. With the remarkable advances, machine …

Cell segmentation is the most significant task in microscopic image analysis as it facilitates
differential cell counting and analysis of sub-cellular structures for diagnosing …

Motivation Live cell segmentation is a crucial step in biological image analysis and is also a
challenging task because time-lapse microscopy cell sequences usually exhibit complex …

Background 3D segmentation is often a prerequisite for 3D object display and quantitative
measurements. Yet existing voxel-based methods do not directly give information on the …

Deep learning technique has made a tremendous impact on medical image processing and
analysis. Typically, the procedure of medical image processing and analysis via deep …

Background: In recent years, there is an increasing number of researchers applying
bioimaging techniques to generate a myriad of biological images. The growing image data …