Abstract
With the progressive development of the computer-aided diagnosis (CAD) systems, analysis of high resolution histopathological images has become more easier. In the proposed study, the effects of different color spaces used in various studies in the literature are investigated for the discrimination of cellular structures from background in histopathological images. For this purpose, performances of k-means, fuzzy c-means and expectation-maximization algorithms are compared in different color spaces. In the experimental results section, different segmentation accuracy metrics are presented in comparative manner.
Keywords
Artificial intelligence
Computer vision
Segmentation
Computer science
Color space
Image segmentation
CAD
Pattern recognition (psychology)
Maximization
Fuzzy logic
Mathematics
Image (mathematics)
Engineering drawing
Subject Areas
AI in cancer detection
·Artificial Intelligence ·Physical Sciences
Digital Imaging for Blood Diseases
·Computer Vision and Pattern Recognition ·Physical Sciences
Medical Image Segmentation Techniques
·Computer Vision and Pattern Recognition ·Physical Sciences
Citations by Year
2017: 1
2019: 1
2020: 1
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