Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma

Berkay Mayalive; Orkun Saylig; Özden Y. Özuysal; Devrim P. Okvur; Behçet Ugur Töreyin; Devrim Ünay

doi:10.1109/TIPTEKNO50054.2020.9299213

Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma

Translated title of the contribution: Automated Analysis of Wound Healing Microscopy Image Series - A Preliminary Study

Berkay Mayalive, Orkun Saylig, Özden Y. Özuysal, Devrim P. Okvur, Behçet Ugur Töreyin, Devrim Ünay

Informatics Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

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.

Translated title of the contribution	Automated Analysis of Wound Healing Microscopy Image Series - A Preliminary Study
Original language	Turkish
Title of host publication	TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728180731
DOIs	https://doi.org/10.1109/TIPTEKNO50054.2020.9299213
Publication status	Published - 19 Nov 2020
Event	2020 Medical Technologies Congress, TIPTEKNO 2020 - Antalya, Turkey Duration: 19 Nov 2020 → 20 Nov 2020

Publication series

Name	TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020

Conference

Conference	2020 Medical Technologies Congress, TIPTEKNO 2020
Country/Territory	Turkey
City	Antalya
Period	19/11/20 → 20/11/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Access to Document

10.1109/TIPTEKNO50054.2020.9299213

Cite this

Mayalive, B., Saylig, O., Özuysal, Ö. Y., Okvur, D. P., Töreyin, B. U., & Ünay, D. (2020). Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma. In TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020 Article 9299213 (TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TIPTEKNO50054.2020.9299213

Mayalive, Berkay ; Saylig, Orkun ; Özuysal, Özden Y. et al. / Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma. TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020. Institute of Electrical and Electronics Engineers Inc., 2020. (TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020).

@inproceedings{56c75106a9da4ea488be839829789d98,

title = "Yara Iyilesmesi Mikroskopi G{\"o}r{\"u}nt{\"u} Serilerinin Otomatik Analizi - Bir {\"O}n-{\c C}alisma",

abstract = "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.",

keywords = "Wound healing, deep learning, image processing, phase-contrast optical microscopy",

author = "Berkay Mayalive and Orkun Saylig and {\"O}zuysal, {{\"O}zden Y.} and Okvur, {Devrim P.} and T{\"o}reyin, {Beh{\c c}et Ugur} and Devrim {\"U}nay",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Medical Technologies Congress, TIPTEKNO 2020 ; Conference date: 19-11-2020 Through 20-11-2020",

year = "2020",

month = nov,

day = "19",

doi = "10.1109/TIPTEKNO50054.2020.9299213",

language = "T{\"u}rk{\c c}e",

series = "TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020",

address = "United States",

}

Mayalive, B, Saylig, O, Özuysal, ÖY, Okvur, DP, Töreyin, BU & Ünay, D 2020, Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma. in TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020., 9299213, TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020, Institute of Electrical and Electronics Engineers Inc., 2020 Medical Technologies Congress, TIPTEKNO 2020, Antalya, Turkey, 19/11/20. https://doi.org/10.1109/TIPTEKNO50054.2020.9299213

Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma. / Mayalive, Berkay; Saylig, Orkun; Özuysal, Özden Y. et al.
TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9299213 (TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma

AU - Mayalive, Berkay

AU - Saylig, Orkun

AU - Özuysal, Özden Y.

AU - Okvur, Devrim P.

AU - Töreyin, Behçet Ugur

AU - Ünay, Devrim

PY - 2020/11/19

Y1 - 2020/11/19

N2 - 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.

AB - 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.

KW - Wound healing

KW - deep learning

KW - image processing

KW - phase-contrast optical microscopy

UR - http://www.scopus.com/inward/record.url?scp=85099448181&partnerID=8YFLogxK

U2 - 10.1109/TIPTEKNO50054.2020.9299213

DO - 10.1109/TIPTEKNO50054.2020.9299213

M3 - Konferans katkısı

AN - SCOPUS:85099448181

T3 - TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020

BT - TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 Medical Technologies Congress, TIPTEKNO 2020

Y2 - 19 November 2020 through 20 November 2020

ER -

Mayalive B, Saylig O, Özuysal ÖY, Okvur DP, Töreyin BU, Ünay D. Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma. In TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9299213. (TIPTEKNO 2020 - Tip Teknolojileri Kongresi - 2020 Medical Technologies Congress, TIPTEKNO 2020). doi: 10.1109/TIPTEKNO50054.2020.9299213

Yara Iyilesmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-Çalisma

Abstract

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