Fuzzy Maximum Intensity Projection (FMIP) in Medical Image Diagnosis

Yutaka Hata1
(Professor Lotfi A. Zadeh)
Berkeley Initiative in Soft Computing

In medical imaging, the typical maximum intensity projection (MIP) method projects the maximum intensity values in a three-dimensional (3D) data set to a two-dimensional (2D) plane. However, since several artifacts are involved in the MIP images, it keeps us from examining the exact shape and state of the region of interest (ROI). We propose a new three-dimensional rendering method called fuzzy maximum intensity projection (FMIP), which projects the higher fuzzy membership degrees of target ROI as the brighter values to a 2D plane. Since the FMIP projects the membership degree of every voxel, the FIMP can provide the exact information of the ROI. This membership degree can be given in a fuzzification algorithm. This appropriate fuzzification enables us to examine the ROI with high accuracy. We applied the FMIP to knee CT and lumbar MR images using our developed fuzzification algorithms. The FMIP of the CT meniscus is useful for diagnosing the meniscal tears. The FMIP of the MR endorrhachis is useful for diagnosing a hernia. Consequently, the comparison between FMIP and MIP showed that FMIP was able to effectively visualize the ROI.

[1]
Y. Hata, M. Terao, S. Kobashi, S. Kanazawa, S. Imawaki, and M. Ishikawa, "Fuzzy Maximum Intensity Projection (FMIP) in Medical Imaging," Proc. Int. Forum on Multimedia and Image Processing (to appear).
[2]
Y. Hata, S. Kobashi, K. Kondo, S. Imawaki, and M. Ishikawa, "Fuzzy Maximum Intensity Projection (FMIP) of MR Endorrhachis Images," Proc. Int. Conf. Knowledge-based Intelligent Information Engineering Systems and Allied Technologies, September 2002.
1Visiting Professor, Himeji Institute of Technology

More information (http://wwwj3.comp.eng.himeji-tech.ac.jp/med) or

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