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Updated: Aug 2, 2026

Biochemical and High Throughput Microscopic Assessment of Fat Mass in Caenorhabditis Elegans
Published on: March 30, 2013
Identification of fat, protein matrix, and water/starch on microscopy images of sausages by a principal component
Achim Kohler1, Vibeke Høst, Grethe Enersen
1Norwegian Food Research Institute, Matforsk, Osloveien 1, Norway. achim.kohler@matforsk.no
Abstract:
A color-based segmentation scheme applied to microscopy images of cryosectioned sausages is proposed. The segmentation scheme is capable of segmenting three different levels on the microscopy images: the fat particles, the protein matrix, and water/starch. The method is based on principal component analysis. A user-friendly program was developed for the manual segmentation of a selection of image pixels by microscopists. Principal component models based on the manually classified pixels are then used to segment fat, protein matrix, and starch/water on microscopy images. The program can also be used as a training tool for microscopists.

