This paper presents a method for the systematically extraction cellular parameters from imaging proteomic datasets in a way suitable for subsequent biological modelling and simulation. This was achieved by capturing the spatial boundaries of cell structures as well as the distribution of its constituents. The model uses the Active Shape Models to parameterize the shape of cellular structures and the Non-Gaussian Texture Model to parameterize spatial distribution of sub-cellular material. Results show the model can extract then generate faithful representations of cellular shapes and textures for a variety of cell types and protein expressions and hence could offer a natural spatial framework for current research on simulating and predicting sub-cellular processes.
Original languageEnglish
Title of host publicationN/A
Number of pages3
Publication statusE-pub ahead of print - 2 Jan 2009
Event IEEE International Conference on Image processing ICIP - Location unknown - please update
Duration: 2 Jan 20092 Jan 2009

Conference

Conference IEEE International Conference on Image processing ICIP
Period2/01/092/01/09

    Research areas

  • biomedical imaging, texture analysis, active shape models, cellular proteomics

ID: 120722