Autofocus System
Autofocus System - Related Videos
11:19
ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth
0 Views •
Cited by 4 •
2017
We present a method for quantifying growth phenotypes of individual yeast cells as they grow into colonies on solid media using time-lapse microscopy termed, One-cell Doubling Evaluation of Living Arrays of Yeast (ODELAY). Population heterogeneity of genetically identical cells growing into colonies can be directly observed and quantified.
11:37
Cellular Redox Profiling Using High-content Microscopy
0 Views •
Cited by 7 •
2017
This paper presents a high-content microscopy workflow for simultaneous quantification of intracellular ROS levels, as well as mitochondrial membrane potential and morphology – jointly referred to as mitochondrial morphofunction – in living adherent cells using the cell-permeant fluorescent reporter molecules 5-(and-6)-chloromethyl-2',7'-dichlorodihydrofluorescein diacetate, acetyl ester (CM-H2DCFDA) and tetramethylrhodamine methylester (TMRM).
11:24
High-throughput Imaging and Analysis Workflow for Evaluating Skin Cell Phenotypes and Proliferation States in Tissue Samples
0 Views •
Cited by 1 •
2025
The combination of iterative-bleaching-extends-multiplexity (IBEX) and a commercial nucleotide labeling assay (Click-iT EdU) enables the detection and categorization of dividing cell types in highly dynamic processes in fixed frozen murine tissue sections. Furthermore, a novel open-source image processing pipeline provides high-throughput image acquisition and analysis.
05:57
A Rapid Automated Protocol for Muscle Fiber Population Analysis in Rat Muscle Cross Sections Using Myosin Heavy Chain Immunohistochemistry
0 Views •
Cited by 13 •
2017
Here, we present a protocol for rapid muscle fiber analyses, which allows improved staining quality, and thereby automatic acquisition and quantification of fiber populations using the freely available software ImageJ.
FAQs
It evaluates image contrast or another focus-related signal and uses that measurement to guide adjustment. A motorized objective, lens, or sample stage changes position, after which the system reassesses the image and continues correction until the signal indicates optimal sharpness. This feedback process allows focus to track changing specimen conditions rather than relying on a fixed setting.
These components provide different ways to change the optical relationship between the microscope and specimen. The system can drive a motorized objective or lens, or move the stage carrying the sample, depending on the instrument configuration. Their shared function is to make controlled positional corrections so image sharpness can be recovered when specimen distance changes.
Contrast gives the system a measurable indicator of focus quality instead of requiring a person to judge sharpness continuously. As specimen movement, thermal drift, or sample-thickness variation changes the imaging geometry, the signal can reveal focus loss and support correction. This helps maintain more consistent image quality throughout extended biological observations.
Manual focusing requires repeated human adjustment whenever the specimen distance or imaging conditions change. An autofocus system performs those corrections automatically by analyzing focus-related information and controlling a motorized optical or sample component. The difference is especially important during long observations, because automated correction reduces manual intervention and helps prevent focus loss during an experiment.
The system first obtains an image or focus-related measurement, evaluates its sharpness, and then changes the position of a motorized objective, lens, or sample stage. It repeats measurement and adjustment until the image reaches optimal sharpness. During an experiment, this workflow can be applied again when movement, drift, or thickness variation alters the focus condition.
Focus can change when the specimen moves, when thermal drift alters the relative position of optical components and the sample, or when sample thickness varies across the observed region. These effects are important in biological microscopy because the ideal focus position may not remain constant. Autofocus correction helps compensate for such changes and supports more stable image acquisition.
It is useful for live-cell imaging, time-lapse microscopy, high-throughput screening, and quantitative analysis. In these settings, repeated or extended image acquisition benefits from consistent focus across observations. By reducing focus loss and manual adjustment, the system helps produce more uniform images for monitoring biological changes and comparing measurements collected during an experiment.