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Adipocytes play an important role in energy and glucose metabolism, serving both as energy storage units as well as endocrine regulators for these processes. Being adipocyte size their major modulator, the measurement of adipocyte cross-sectional surface area has been widely used to provide accurate and reproducible characterization of metabolic-related diseases like obesity, diabetes and various cardiovascular diseases. The direct measurement of adipocyte size by microscopy is widely used, although the method is tedious and time consuming. Computer-assisted image analysis can overcome most of the disadvantages associated with this technique.

Wimasis Adipose tool is designed to generate objective and reproducible quantification of adipocyte sizes in hematoxylin and eosin (H&E) stained histological sections. The quantification is based on the detection of the whole cell population and the measurement of the cross-sectional area distribution of the detected cell adipocytes. This recognition is possible thanks to our fast high-end image processing algorithms, which allow an automatic accurate analysis of the cell cultures in record time.

Wimasis Adipose tool uses as input H&E stained histological section microscope images of white adipose tissue. Importers for whole-slide images or virtual images (.svs, .vms, .vmu, .scn, .mrxs, tiled .tif) can be developed upon request.
Adipose Tissue image granted by the ZIEL Molecular Nutritional Medicine, Technische Universität München.
  • Maria Rödiger, Martin W. Werno , Ilka WilhelmiEmail the author Ilka Wilhelmi , Christian BaumeierEmail the a, Deike Hesse, Nina Wettschureck, Stefan Offermann, Kyungyeun Song , Michael Krauß, Annette Schürmann. Adiponectin release and insulin receptor targeting share trans-Golgi-dependent endosomal trafficking routes Molecular Metabolism. November 2017
  • Theresa Schöttl, Lisa Kappler, Katharina Braun, Tobias Fromme, and Martin Klingenspor. Limited mitochondrial capacity of visceral versus subcutaneous white adipocytes in male C57BL/6N mice Endocrinology. December 2014
  • Maria Rohm, Anke Sommerfeld, Daniela Strzoda, Allan Jones, Tjeerd P. Sijmonsma, Gottfried Rudofsky, Christian Wolfrum, Carsten Sticht, Norbert Gretz, Maximilian Zeyda, Lukas Leitner, Peter P. Nawroth, Thomas M. Stulnig, Mauricio Berriel Diaz, Alexandros Vegiopoulos, Stephan Herzig. Transcriptional Cofactor TBLR1 Controls Lipid Mobilization in White Adipose Tissue Cell Metabolism. April 2013
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Please, choose the quantity
  • 100 images 350.00 €
  • 250 images 750.00 €
  • 500 images 1,000.00 €
  • 1000 images 1,500.00 €
  • 2000 images 2,500.00 €
  • 5000 images 6,000.00 €
  • 10000 images 10,000.00 €
  • 20000 images 18,000.00 €
(Tax free)
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Analysis data contain
  • ✔ Total cell count: total number of detected adipocytes in the image.
  • ✔ Cell area: list of the area of each adipocyte (in micrometers if conversion factor is provided)
  • ✔ Mean cell area: mean area of the adipocytes
  • ✔ STD cell area: standard deviation of the adipocytes
  • ✔ Mean equivalent diameter: mean of the adipocytes
  • ✔ STD equivalent diameter: standard deviation of the adipocytes
Would you like to get any other parameter? Ask for it!
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Case studies
Technical University of Munich
Molecular Food Technology and Safety
At the chair of Molecular Nutritional Medicine we study the balance between energy intake and expenditure. Thermogenic brown adipocytes profoundly contribute to the latter by dissipating nutrient energy in the form of heat. Characteristic features of brown as compared to white adipocytes are the lower size and greater number of lipid droplets as well as the smaller overall cell size.

Wimasis has developed a custom solutiom to us to automatically determine adipocyte size and number in images of histological sections that saves us hours and hours of manual counting and measuring. Even better, in cooperation with Wimasis, we established an image analysis procedure enabling us to quantify lipid droplet size and number in images of cultured adipocytes. A task that is impossible to perform manually and far less efficient with off-the-shelf particle recognition software in our hands.

With Wimasis image analyses we do not only save a lot of time, but are even able to extract more quantitative information out of every image we take.
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