25 April 1997 Fast fuzzy segmentation of magnetic resonance images: a prerequisite for real-time rendering
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In order to obtain a meaningful 3D rendered image from Magnetic Resonance Image (MRI) data, it is first necessary to classify each voxel in the data set according to its corresponding tissue type. Existing techniques require long processing times and often need expert interaction. This paper describes a new method for automatic and real-time fuzzy segmentation. A histogram of reduced resolution grey scale data is first generated and used as input to a simplified version of the Fuzzy c-Means (FCM) algorithm. A new color blending scheme is proposed to allow the classified data to be displayed. When processing a 3D MRI data set, the original FCM algorithm took over 5 hours, whereas the new method took less than one second. Furthermore, the resulting images from both the original and the new methods were indistinguishable. Assessment of the results by an expert radiologist showed that the segmented structures corresponded very accurately with the actual anatomy. In addition, the color blended display enabled poorly defined boundaries and structures to be clearly identified.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Norman R. Smith, Norman R. Smith, Richard I. Kitney, Richard I. Kitney, } "Fast fuzzy segmentation of magnetic resonance images: a prerequisite for real-time rendering", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274093; https://doi.org/10.1117/12.274093

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