An interactive tool for the segmentation of multimodal medical images

This paper describes a software application to segment multimodal biomedical images in 2D and to render the final result in 3D. It makes use of the false-colouring method for image fusion and of unsupervised clustering algorithms. It includes pre-processing and post-processing tools, such as classical morphological operators. Results are presented from original MRI data sets in T1, T2 and STIR modalities.

[1]  L O Hall,et al.  Review of MR image segmentation techniques using pattern recognition. , 1993, Medical physics.

[2]  J H Simon,et al.  Quantitation of grey matter, white matter, and cerebrospinal fluid from spin-echo magnetic resonance images using an artificial neural network technique. , 1994, Medical physics.

[3]  Lawrence O. Hall,et al.  Mri Segmentation Using Supervised And Unsupervised Methods , 1991, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991.

[4]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[5]  Francesco Masulli,et al.  Fuzzy Clustering Methods for the Segmentation of Multimodal Medical Images , 2000 .

[6]  King-Sun Fu,et al.  Handbook of pattern recognition and image processing , 1986 .

[7]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[8]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .

[9]  A. Alavi,et al.  Analysis of brain and cerebrospinal fluid volumes with MR imaging. Part I. Methods, reliability, and validation. , 1991, Radiology.

[10]  Guido Gerig,et al.  Unsupervised tissue type segmentation of 3D dual-echo MR head data , 1992, Image Vis. Comput..

[11]  P.K Sahoo,et al.  A survey of thresholding techniques , 1988, Comput. Vis. Graph. Image Process..

[12]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.