Özet
Collective cell analysis from microscopy image series is important for wound healing research. Computer-based automation of such analyses may help in rapid acquisition of reliable and reproducible results. In this study phase-contrast optical microscopy image series of an in-vitro wound healing essay is manually delineated by two experts and its analysis is realized, traditional image processing and deep learning based approaches for automated segmentation of wound area are developed and their performance comparisons are carried out.
Tercüme edilen katkı başlığı | Automated Analysis of Wound Healing Microscopy Image Series - A Preliminary Study |
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Orijinal dil | Türkçe |
Ana bilgisayar yayını başlığı | TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020 |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Elektronik) | 9781728180731 |
DOI'lar | |
Yayın durumu | Yayınlandı - 19 Kas 2020 |
Etkinlik | 2020 Medical Technologies Congress, TIPTEKNO 2020 - Antalya, Turkey Süre: 19 Kas 2020 → 20 Kas 2020 |
Yayın serisi
Adı | TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020 |
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???event.eventtypes.event.conference??? | 2020 Medical Technologies Congress, TIPTEKNO 2020 |
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Ülke/Bölge | Turkey |
Şehir | Antalya |
Periyot | 19/11/20 → 20/11/20 |
Bibliyografik not
Publisher Copyright:© 2020 IEEE.
Keywords
- Wound healing
- deep learning
- image processing
- phase-contrast optical microscopy