Generation of 3D Digital Phantoms of Colon Tissue

Although segmentation of biomedical image data has been paid a lot of attention for many years, this crucial task still meets the problem of the correctness of the obtained results. Especially in the case of optical microscopy, the ground truth (GT), which is a very important tool for the validation of image processing algorithms, is not available. We have developed a toolkit that generates fully 3D digital phantoms, that represent the structure of the studied biological objects. While former papers concentrated on the modelling of isolated cells (such as blood cells), this work focuses on a representative of tissue image type, namely human colon tissue. This phantom image can be submitted to the engine that simulates the image acquisition process. Such synthetic image can be further processed, e.g. deconvolved or segmented. The results can be compared with the GT derived from the digital phantom and the quality of the applied algorithm can be measured.

[1]  Anders Heyden,et al.  A fast algorithm for level set-like active contours , 2003, Pattern Recognit. Lett..

[2]  H. Netten,et al.  FISH and chips: automation of fluorescent dot counting in interphase cell nuclei. , 1997, Cytometry.

[3]  Franz Aurenhammer,et al.  Voronoi diagrams—a survey of a fundamental geometric data structure , 1991, CSUR.

[4]  Edward R. Dougherty,et al.  Simulation Toolbox for 3D-FISH Spot-Counting Algorithms , 2002, Real Time Imaging.

[5]  Akinobu Shimizu,et al.  3D extension of Haralick texture features for medical image analysis , 2007 .

[6]  H. Netten,et al.  Fluorescent dot counting in interphase cell nuclei , 1996 .

[7]  Ting Zhao,et al.  Automated learning of generative models for subcellular location: Building blocks for systems biology , 2007, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[8]  D Sudar,et al.  Efficient, interactive, and three-dimensional segmentation of cell nuclei in thick tissue sections. , 1998, Cytometry.

[9]  Michal Kozubek,et al.  Generation of digital phantoms of cell nuclei and simulation of image formation in 3D image cytometry , 2009, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[10]  Ken Perlin,et al.  [Computer Graphics]: Three-Dimensional Graphics and Realism , 2022 .

[11]  M Kozubek,et al.  Comparative transcriptome maps: a new approach to the diagnosis of colorectal carcinoma patients using cDNA microarrays , 2006, Clinical genetics.

[12]  Pekka Ruusuvuori,et al.  Computational Framework for Simulating Fluorescence Microscope Images With Cell Populations , 2007, IEEE Transactions on Medical Imaging.

[13]  J Strackee,et al.  Largest contour segmentation: a tool for the localization of spots in confocal images. , 1996, Cytometry.