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|Title:||Cascade pattern recognition structure for improving quantitative assessment of estrogen receptor status in breast tissue carcinomas|
Κάβουρας, Διονύσης Α.
Καγκάδης, Γεώργιος Χ.
Νικηφορίδης, Γεώργιος Σ.
|Item type:||Journal article|
|Keywords:||Histopathology;Image analysis;Ιστοπαθολογία;Ανάλυση εικόνας|
|Publisher:||Journal of Reproductive Medicine|
|Abstract:||OBJECTIVE: To develop and validate a computer-based approach for the quantitative assessment of estrogen receptor (ER) status in breast tissue specimens for breast cancer management. STUDY DESIGN: Microscopy images of 32 immunohistochemically (IHC) stained specimens of breast cancer biopsies were digitized and were primarily assessed for ER status (percentage of positively stained nuclei) by a histopathologist. A pattern recognition system was designed for automatically assessing the ER status of the IHC-stained specimens. Nuclei were automatically segmented from background by a pixel-based unsupervised clustering algorithm and were characterized as positively stained or unstained by a supervised classification algorithm. This cascade structure boosted the system's classification accuracy. RESULTS: System performance in correctly characterizing the nuclei was 95.48%. When specifying each case's ER status, system performance was statistically not significantly different to the physician's assessment (p = 0.13); when ranking each case to a particular 5-scale ER-scoring system (giving the chance of response to endocrine treatment), the system's score and the physician's score were in agreement in 29 of 32 cases. CONCLUSION: The need for reliable and operator independent ER-status estimation procedures may be served by the design of efficient pattern recognition systems to be employed as support opinion tools in clinical practice.|
|Citation:||Kostopoulos, S., Cavouras, D., Daskalakis, A., Kagadis, G., Kalatzis, I., et al. (August 2008). Cascade pattern recognition structure for improving quantitative assessment of ER-status in breast tissue carcinomas. Analytical and Quantitative Cytology and Histology. 30(4). pp. 218-225. Journal of Reproductive Medicine: 2008.|
|Journal:||Analytical and Quantitative Cytology and Histology|
|Type of Journal:||With a review process (peer review)|
|License:||Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες|
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