Image segmentation method

Details Image segmentation method Image segmentation method

2005-01-04

2005-01-04

Werner, Brian (Department: 2621)

Image analysis

Image segmentation

C382S128000, C382S171000, C382S225000, C382S299000

Reexamination Certificate

active

06839462

ABSTRACT:
A method of producing a simulated 3-dimensional image, the method comprising: assimilating 2-dimensional image data, e.g. from MR image slices; assigning a feature, e.g. gray scale value to each datum; reducing the resolution of each gray scale value of the data; generating a histogram of the reduced resolution gray scale data; performing a fast fuzzy c-means clustering on the histogram data. The resolution of each pixel object in the images may be reduced from 12 bit to 8 bit resolution, and the histogram may be generated from these. Subsequently a value may be assigned for each entry in the histogram, each entry value being equal to the number of objects of any given feature (e.g. gray scale) in the reduced resolution (8 bit) image. The image may be displayed using a novel color blending technique. A 3D image is produced quickly and without supervisory intervention and can be used in endoscopic surgery and in diagnostic methods as well as in understanding healthy anatomical features better.

REFERENCES:
patent: 5425368 (1995-06-01), Brandt
patent: 5426684 (1995-06-01), Gaborski et al.
patent: 6064770 (2000-05-01), Scarth et al.
Kandel, A.; “Fuzzy Techniques in Pattern Recognition”; John Wiley & Sons, New York, 1982; pp.
Bezdek, James C., “Pattern Recognition with Fuzzy Objective Function Algorithms”; Plenum Press, New York, 1981.
Lim and Lee, “On the Color Image Segmentation Algorithm Based on the Thresholding and the Fuzzy C-Means Techniques” Pattern Recognition, vol. 23, No. 9, 1990, Oxford GB, pp. 935-952, XP000159058 see page 937, right-hand column, line 3—see p. 940, left-hand column, line 3 see p. 941, left-hand column, line 9—right-hand column, line 35.
Hall L O et al: “A Comparison of Neural Network and Fuzzy Clustering Techniques in Segmenting Magnetic Resonance Images of the Brain” IEEE Transactions on Neural Networks, vol. 3, No. 5, Sep. 1, 1992, pp. 672-682, XP000299154 see p. 676, left-hand column, line 12—right-hand column, line 26.
Jantzen J et al: “Image Segmentation Based on Scaled Fuzzy Membership Functions” 2ndIEEE International Conference on Fuzzy Systems, vol. 2, Mar. 28, 1993-Apr. 1, 1993, New-York NY US, pp. 714-718, XP000371497 see the whole document.
Takashi Mochizuki et al: “Classification of Ultrasonic Images Using Fuzzy Reasoning and Spatial Smoothing Effect of Textural Features” Electronics & Communications in Japan, Part III—Fundamental Electronic Science, vol. 78, No. 6, Jun. 1, 1995, pp. 62-76, XP000551801 see the whole document.

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