Upcoming: Drosophila Vial Scanner

In-situ imaging of Drosophila pupae in less than 2 seconds for automated measurement of size or movement

Drosophila Vial Scanner
Drosophila Vial Scanner
Drosophila Vial Scanner
Scanned image
Analysis

Features

Vial Scanner for in-situ imaging of Drosophila pupae for automated measurement of size or movement

  • Monochrome camera, LED background illumination
  • Imaging of the inner surface of the vial during a rotational movement
  • Field of view (image height): 77 mm, resolution: 15 μm/pixel (1693 dpi) 
  • Scan duration: approx. 2 seconds  
  • Automatic barcode recognition and file storage

Description

The Drosophilae Vial Scanner was developped for the in-situ imaging of Drosophila pupae and for automated measurement of their size. The scan procedure only takes about 2 s.

How it works

The Drosophila vial scanner consists of a high-resolution monochrome line scan camera system (C), a sample holder mounted on a rotary drive (B), an LED backlight (A), and an auxiliary light for the barcode at the lower edge of the sample. During the rotation of the vial, the line-scan camera captures an image of the inner surface of the vial. The system also includes control software for the PC connected via Ethernet. It includes the automatic transformation of the slightly conical vial surface into Cartesian coordinates as well as the recognition of the barcode at the lower edge of the image. The image data is saved in lossless .png format, the barcode determines the file name. In batch mode, the scanning process is triggered at the touch of a button. A scan process takes less than two seconds.

What the scanner can do

The Drosophila Vial Scanner is designed to make it much easier to observe the growth or movement of Drosophila pupae. Without having to remove the pupae from the vial in which they are reared, the scanner delivers high-contrast, high-resolution and calibrated images to your evaluation software in seconds.

We recommend CellProfiler, a free, open-source software for quantitative analysis of biological images: https://cellprofiler.org/gettingstarted .