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An Advanced Image Analysis Tool for the Quantification and Characterization of Breast Cancer in Microscopy Images.

The paper presents an advanced image analysis tool for the accurate and fast characterization and quantification of cancer and apoptotic cells in microscopy images. The proposed tool utilizes adaptive thresholding and a Support Vector Machines classifier. The segmentation results are enhanced throug...

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Published in:Journal of Medical Systems Vol. 39; no. 3; pp. 1 - 14
Main Authors: Goudas, Theodosios, Maglogiannis, Ilias
Format: algorithm equations & formulas pictorial research tables/charts Journal Article
Published: Springer Nature Mar2015
Online Access:View this record in EBSCOhost
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      dt: Mar2015
      vid: 39
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-015-0225-3
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        atl: An Advanced Image Analysis Tool for the Quantification and Characterization of Breast Cancer in Microscopy Images.
      aug:
        au:
          Goudas, Theodosios
          Maglogiannis, Ilias
        affil: Department of Digital Systems, University of Piraeus, Grigoriou Lampraki 126 PC 18532 Piraeus Greece
      sug:
        subj:
          Breast Neoplasms Diagnosis
          Breast Neoplasms Pathology
          Image Interpretation, Computer Assisted Evaluation
          Microscopy, Virtual
          Apoptosis
          Breast Neoplasms Classification
          Registries, Disease
          Animal Studies
          Mice
          Models, Biological
          Evaluation Research
          Descriptive Statistics
          Cell Count
          Cytological Techniques, Automated
      ab: The paper presents an advanced image analysis tool for the accurate and fast characterization and quantification of cancer and apoptotic cells in microscopy images. The proposed tool utilizes adaptive thresholding and a Support Vector Machines classifier. The segmentation results are enhanced through a Majority Voting and a Watershed technique, while an object labeling algorithm has been developed for the fast and accurate validation of the recognized cells. Expert pathologists evaluated the tool and the reported results are satisfying and reproducible.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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