title: How to improve microscopic images obtained with consumer-type digital cameras.
abstract: OBJECTIVE
  Digital imaging is useful in conventional photography because it immediately provides images, and the image quality can be improved afterwards by the use of computer programs. The major disadvantages of consumer-type digital cameras mounted on microscopes are (i) unequal illumination through the image, and (ii) a coloured background. A computer program was specifically adapted and refined to improve images obtained with consumer-type digital cameras mounted on microscopes.
  
  
  RESULTS
  An approach using a division operation between the specimen image and a background image leads to homogeneous illumination throughout the image, with automatically corrected brightness and white background. The correct colour spectrum is preserved by correction of the histogram. This approach was obtained from the freeware computer program 'Image Arithmetic'. In a test, three different consumer-type digital cameras (Sony, Nikon, Olympus) on different microscopes were used to obtain images of different types of histological specimens (cervical smear, bone marrow biopsy, and colonic biopsy). The computer program dramatically improved the quality of images obtained with all tested cameras.
  
  
  CONCLUSIONS
  Using this approach, even low-cost digital cameras mounted on microscopes produce brilliant images with homogeneous illumination and a white background, the image quality being comparable with expensive cameras especially designed for microscopes.
authors.affiliation: Department of Pathology, University of Graz, School of Medicine, Austria. peter.regitnig@uni-graz.at
authors.forename: P
authors.initials: P
authors.lastname: Regitnig
authors.forename: R
authors.initials: R
authors.lastname: van Paasen
authors.forename: O
authors.initials: O
authors.lastname: Tsybrovskyy
mesh_terms: D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D010784:Photomicrography / Q000191:economics / Q000295:instrumentation* / Q000379:methods; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D012984:Software