Microscopy imaging enables researchers to gain insight into complex processes not
understood so far. Reducing the time to insight for researchers requires highly automated …

Detection of cells and particles in microscopy images is a common and challenging task. In
recent years, detection approaches in computer vision achieved remarkable improvements …

Deep learning has become one of the most important topics in Computer Science, and
recently it proved to deliver outstanding performances in the field of Computer Vision …

Deep learning has demonstrated significant potential in particle size measurement across
various fields, including mining, agriculture, and cell processing. However, its performance …

Automated nanoparticle phenotyping is a critical aspect of high-throughput drug research,
which requires analyzing nanoparticle size, shape, and surface topography from microscopy …

This work presents the development and implementation of a deep learning-based workflow
for autonomous image analysis in nanoscience. A versatile, agnostic, and configurable tool …

Abstract 3D particle streak velocimetry (3D-PSV) and surface flow visualization using tufts
both require the detection of curve segments, particle streaks or tufts, in images. We propose …

High-content microscopy led to many advances in biology and medicine. This fast emerging
technology is transforming cell biology into a big data driven science. Computer vision …

Motivation An automated counting of beads is required for many high-throughput
experiments such as studying mimicked bacterial invasion processes. However, state-of-the …

Automatic detection and segmentation of objects in 2D and 3D microscopy data is important
for countless biomedical applications. In the natural image domain, spatial embedding …