New model for medical image analysis based on computational intelligence

Jens Hiltner; Madjid Fathi; Bernd Reusch

doi:10.1117/12.387638

6 June 2000 New model for medical image analysis based on computational intelligence

Jens Hiltner, Madjid Fathi, Bernd Reusch

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387638
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

Medical image data contain several types of uncertain or vague information. Therefore, the knowledge about the data is also vague. Consequently, for the segmentation and classification of the image data the use of vague knowledge should be allowed. Finally, the optimization of such systems dealing with vague information should also be done automatically. Using fuzzy descriptions for the segmentation and analysis of medical image data has provided better results than the exclusive use of standard methods. More often, structures can be segmented and classified more adequately. Applications have been developed to segment brain structures and tumors in MRI- data. By applying neural networks, good results for the step of image improvement (pre-processing) and determination of regions of interest (ROI) in image data were obtained. Even more the classification of structures with neural networks has shown also good results. The optimization of the knowledge base was done with evolution strategies. Therefore, the optimization time was reduced to a fraction of the time needed for a manual optimization.

Citation Download Citation

Jens Hiltner, Madjid Fathi, and Bernd Reusch "New model for medical image analysis based on computational intelligence", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387638

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