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笔记@Lung Cancer Detection on CT S

笔记@Lung Cancer Detection on CT S

作者: JChen_95 | 来源:发表于2017-01-27 10:32 被阅读47次

    Lung Cancer Detection on CT Scan Images A Review on the Analysis Techniques

    0. Introduction

    1. Review of existing nodule detection methods

    1.1 Pre_processing

    1.2 Segmentation

    • 2D-based segmentation

    ① Thresholding based methods[7][8][11][10][17][26][76][99]

    ② Stochastic methods[22][40]

    ③ Region based methods[1][18][20][28][59][62][63][79][80]

    ④ Contour based methods[9][44][47][49][77][82][95]

    ⑤ Learning based methods[4][19][45][58][90]

    • 3D-based approaches

    ① Thresholding methods[91][92][96]

    ② Mathematical morphology[30][38][52][53][56][57][69]

    ③ Region-based methods

    • Region growing[19][21][37][54][55]
    • Graph-based methods(Graph-cut)[97][98]

    ④ Model-based methods(Deformable models)[14][25][24][29][47][48][83][93][258]

    ⑤ Dynamic programming[86][87]

    1.3 Nodule extraction and classification

    • Fuzzy classification and Neural Networks---[2][4][12][13][19][43][52][61][62][73][86]
    • K-Nearest Neighbor---[25][50][66][81][96]
    • Support vector machines---[36][46][65][70]
    • Linear Discriminant Analysis---[5][33][41][49][67]

    2. Conclusion

    • Developing new and better techniques of contrast enhancement;
    • selecting better criteria for performance evaluation is also needed.

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        本文标题:笔记@Lung Cancer Detection on CT S

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