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  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
  • View Item
  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
  • View Item
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Unsupervised detection of fibrosis in microscopy images using fractals and fuzzy c-means clustering

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Author
Tasoulis, S. K.; Maglogiannis, I.; Plagianakos, V. P.
Date
2012
DOI
10.1007/978-3-642-33409-2_40
Keyword
Cluster Analysis
Fractal Dimension
Fuzzy Clustering
Image Analysis
Automated assessment
Computer assisted
Fluorescent probes
Fuzzy C means clustering
Fuzzy clustering method
Idiopathic pulmonary fibrosis
Medical images
Medical research
Microscopic image
Microscopy images
Unsupervised detection
Artificial intelligence
Diagnosis
Fuzzy systems
Medical imaging
Metadata display
Abstract
The advances in improved fluorescent probes and better cameras in collaboration with the advent of computers in imaging and image analysis, assist the task of diagnosis in many fields of biologic and medical research. In this paper, we introduce a computer-assisted image characterization tool based on a Fuzzy clustering method for the quantification of degree of Idiopathic Pulmonary Fibrosis (IPF) in medical images. The implementation of this algorithmic strategy is very promising concerning the issue of the automated assessment of microscopic images of lung fibrotic regions. © 2012 IFIP International Federation for Information Processing.
URI
http://hdl.handle.net/11615/33576
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  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]

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