Performance comparison of clustering and thresholding algorithms for tuberculosis bacilli segmentation
Image segmentation is a key step in most medical image analysis. However, the process is particularly difficult due to limitation of the imaging equipments and variation in biological system. Therefore, accurate and robust segmentation are important for quantitative assessment of medical images in o...
الحاوية / القاعدة: | IEEE CITS 2012 - 2012 International Conference on Computer, Information and Telecommunication Systems |
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المؤلف الرئيسي: | Osman M.K.; Mashor M.Y.; Jaafar H. |
التنسيق: | Conference paper |
اللغة: | English |
منشور في: |
2012
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الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864253627&doi=10.1109%2fCITS.2012.6220378&partnerID=40&md5=480a1473dfd9baf2a1dd75a1bde65764 |
مواد مشابهة
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Segmentation of tuberculosis bacilli in Ziehl-Neelsen-stained tissue images based on K-mean clustering procedure
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Colour image segmentation of tuberculosis bacilli in Ziehl-Neelsen-stained tissue images using moving k-mean clustering procedure
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منشور في: (2010) -
Detection of tuberculosis bacilli in tissue slide images using HMLP network trained by Extreme Learning Machine
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منشور في: (2012) -
Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine
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منشور في: (2011) -
Hybrid multilayered perceptron network trained by modified recursive prediction error-extreme learning machine for tuberculosis bacilli detection
بواسطة: Osman M.K.; Mashor M.Y.; Jaafar H.
منشور في: (2011)