Segmentation of Total Cell Area in Brightfield Microscopy Images

被引:8
|
作者
Cepa, Martin [1 ]
机构
[1] Contipro As, Dolni Dobrouc 401, Dolni Dobrou 56102, Czech Republic
关键词
brightfield segmentation; microscopy; ImageJ; Fiji; image analysis; cells;
D O I
10.3390/mps1040043
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Segmentation is one of the most important steps in microscopy image analysis. Unfortunately, most of the methods use fluorescence images for this task, which is not suitable for analysis that requires a knowledge of area occupied by cells and an experimental design that does not allow necessary labeling. In this protocol, we present a simple method, based on edge detection and morphological operations, that separates total area occupied by cells from the background using only brightfield channel image. The resulting segmented picture can be further used as a mask for fluorescence quantification and other analyses. The whole procedure is carried out in open source software Fiji.
引用
收藏
页码:1 / 8
页数:8
相关论文
共 50 条
  • [1] Automatic segmentation of adherent biological cell boundaries and nuclei from brightfield microscopy images
    Rehan Ali
    Mark Gooding
    Tünde Szilágyi
    Borivoj Vojnovic
    Martin Christlieb
    Michael Brady
    Machine Vision and Applications, 2012, 23 : 607 - 621
  • [2] Automatic segmentation of adherent biological cell boundaries and nuclei from brightfield microscopy images
    Ali, Rehan
    Gooding, Mark
    Szilagyi, Tuende
    Vojnovic, Borivoj
    Christlieb, Martin
    Brady, Michael
    MACHINE VISION AND APPLICATIONS, 2012, 23 (04) : 607 - 621
  • [3] Comparing Deep Learning Performance for Chronic Lymphocytic Leukaemia Cell Segmentation in Brightfield Microscopy Images
    Vasinkova, Marketa
    Dolezi, Vit
    Vasinek, Michal
    Gajdos, Petr
    Kriegova, Eva
    BIOINFORMATICS AND BIOLOGY INSIGHTS, 2024, 18
  • [4] Neurosphere Segmentation in Brightfield Images
    Cheng, Jierong
    Xiong, Wei
    Chia, Shue Ching
    Lim, Joo Hwee
    Sankaran, Shvetha
    Ahmed, Sohail
    MEDICAL IMAGING 2014: IMAGE PROCESSING, 2014, 9034
  • [5] Evaluating Very Deep Convolutional Neural Networks for Nucleus Segmentation from Brightfield Cell Microscopy Images
    Ali, Mohammed A. S.
    Misko, Oleg
    Salumaa, Sten-Oliver
    Papkov, Mikhail
    Palo, Kaupo
    Fishman, Dmytro
    Parts, Leopold
    SLAS DISCOVERY, 2021, 26 (09) : 1125 - 1137
  • [6] ArtSeg—Artifact segmentation and removal in brightfield cell microscopy images without manual pixel-level annotations
    Mohammed A. S. Ali
    Kaspar Hollo
    Tõnis Laasfeld
    Jane Torp
    Maris-Johanna Tahk
    Ago Rinken
    Kaupo Palo
    Leopold Parts
    Dmytro Fishman
    Scientific Reports, 12
  • [7] Advanced phase-based segmentation of multiple cells from brightfield microscopy images
    Ali, Rehan
    Gooding, Mark
    Christlieb, Martin
    Brady, Michael
    2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4, 2008, : 181 - +
  • [8] ArtSeg-Artifact segmentation and removal in brightfield cell microscopy images without manual pixel-level annotations
    Ali, Mohammed A. S.
    Hollo, Kaspar
    Laasfeld, Tonis
    Torp, Jane
    Tahk, Maris-Johanna
    Rinken, Ago
    Palo, Kaupo
    Parts, Leopold
    Fishman, Dmytro
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [9] Segmentation and Tracking of Mammary Epithelial Organoids in Brightfield Microscopy
    Hradecka, Lucia
    Wiesner, David
    Sumbal, Jakub
    Koledova, Zuzana Sumbalova
    Maska, Martin
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2023, 42 (01) : 281 - 290
  • [10] Automated Segmentation of Cell Structure in Microscopy Images
    Kerrison, Nicole
    Bulpitt, Andy
    PROCEEDINGS OF THE 2014 9TH INTERNATIONAL CONFERENCE ON COMPUTER VISION, THEORY AND APPLICATIONS (VISAPP 2014), VOL 3, 2014, : 98 - 105