Faz Kontrast Optik Mikroskopi Zaman Serisi Görüntülerinde Hücrelerin Otomatik Bölütlenmesi
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Date
2019
Authors
Okvur, Devrim Pesen
Yalçın Özuysal, Özden
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
Faz kontrast optik mikroskopi hücrelerin canlı
ortamlarında zamana bağlı incelenmesi için tercih edilen görüntüleme yöntemidir. Bu yöntem ile elde edilen zaman serisi görüntülerinde hücrelerin bölütlenmesi işi hücre biyolojisi araştırmacılarının çözümüne ihtiyaç duyduğu emek yoğun ve zaman alan bir iştir. Bu çalışmada faz kontrast optik mikroskopi zaman serilerinde hücrelerin otomatik bölütlenmesi için geleneksel görüntü işleme ve derin öğrenme temelli yöntemler önerilmiş ve başarımları elle işaretlenmiş veri kümelerinde nicel olarak ölçülmüştür.
Phase contrast optical microscopy is a preferred imaging technique for live-cell, temporal analysis. Segmentation of cells from time series data acquired with this technique is a labor-intensive and time-consuming task that cell biology researchers need solution for. In this study traditional image processing and deep learning based approaches for automated cell segmentation from phase contrast optical microscopy time series are presented, and their performances are evaluated against manually annotated datasets. © 2019 IEEE.
Phase contrast optical microscopy is a preferred imaging technique for live-cell, temporal analysis. Segmentation of cells from time series data acquired with this technique is a labor-intensive and time-consuming task that cell biology researchers need solution for. In this study traditional image processing and deep learning based approaches for automated cell segmentation from phase contrast optical microscopy time series are presented, and their performances are evaluated against manually annotated datasets. © 2019 IEEE.
Description
2019 Medical Technologies Congress, TIPTEKNO 2019; Palm Wings Ephesus HotelIzmir; Turkey; 3 October 2019 through 5 October 2019
Keywords
Cell segmentation, Deep learning, Phase contrast optical microscopy, SegNet, Time series
Fields of Science
0301 basic medicine, 0303 health sciences, 03 medical and health sciences
Citation
WoS Q
N/A
Scopus Q
N/A

OpenCitations Citation Count
3
Source
Tıp Teknolojileri Kongresi, TIPTEKNO 2019
Volume
Issue
Start Page
1
End Page
4
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Citations
CrossRef : 2
Scopus : 6
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Mendeley Readers : 8
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