AUTOMATIC SEGMENTATION OF EMBRYONIC HEART IN TIME-LAPSE FLUORESCENCE MICROSCOPY IMAGE SEQUENCES

被引:0
|
作者
Kramer, P. [1 ]
Boto, F. [1 ]
Wald, D. [1 ]
Bessy, F. [1 ]
Paloc, C. [1 ]
Callol, C. [2 ]
Letamendia, A. [2 ]
Ibarbia, I. [2 ]
Holgado, O. [2 ]
Virto, J. M. [2 ]
机构
[1] Vicomtech, Paseo Mikeletegi 57, San Sebastian 20009, Spain
[2] Biobide, San Sebastian 20009, Spain
来源
BIOSIGNALS 2010: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING | 2010年
关键词
Segmentation; Fluorescent microscopy images; Embryonic heart; ZEBRAFISH;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Embryos of animal models are becoming widely used to study cardiac development and genetics. However, the analysis of the embryonic heart is still mostly done manually. This is a very laborious and expensive task as each embryo has to be inspected visually by a biologist. We therefore propose to automatically segment the embryonic heart from high-speed fluorescence microscopy image sequences, allowing morphological and functional quantitative features of cardiac activity to be extracted. Several methods are presented and compared within a large range of images, varying in quality, acquisition parameters, and embryos position. Although manual control and visual assessment would still be necessary, the best of our methods has the potential to drastically reduce biologist workload by automating manual segmentation.
引用
收藏
页码:121 / 126
页数:6
相关论文
共 50 条
  • [31] Time-Lapse Image Fusion
    Estrada, Francisco J.
    COMPUTER VISION - ECCV 2012, PT II, 2012, 7584 : 441 - 450
  • [32] Automatic improvement of deep learning-based cell segmentation in time-lapse microscopy by neural architecture search
    Zhu, Yanming
    Meijering, Erik
    BIOINFORMATICS, 2021, 37 (24) : 4844 - 4850
  • [33] Automated identification of axonal growth cones in time-lapse image sequences
    Keenan, TM
    Hooker, A
    Spilker, ME
    Li, NZ
    Boggy, GJ
    Vicini, P
    Folch, A
    JOURNAL OF NEUROSCIENCE METHODS, 2006, 151 (02) : 232 - 238
  • [34] MitoGen: A Framework for Generating 3D Synthetic Time-Lapse Sequences of Cell Populations in Fluorescence Microscopy
    Svoboda, David
    Ulman, Vladimir
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2017, 36 (01) : 310 - 321
  • [35] NEURITE RECONSTRUCTION FROM TIME-LAPSE SEQUENCES USING CO-SEGMENTATION
    Gulyanon, S.
    Sharifai, N.
    Kim, M. D.
    Chiba, A.
    Tsechpenakis, G.
    2017 IEEE 14TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2017), 2017, : 410 - 414
  • [36] Time-lapse microscopy of brain development
    Köster, RW
    Fraser, SE
    ZEBRAFISH: 2ND EDITION CELLULAR AND DEVELOPMENTAL BIOLOGY, 2004, 76 : 207 - +
  • [37] Spatio-Temporal Mitosis Detection in Time-Lapse Phase-Contrast Microscopy Image Sequences: A Benchmark
    Su, Yu-Ting
    Lu, Yao
    Liu, Jing
    Chen, Mei
    Liu, An-An
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021, 40 (05) : 1319 - 1328
  • [38] Multi-Grained Random Fields for Mitosis Identification in Time-Lapse Phase Contrast Microscopy Image Sequences
    Liu, An-An
    Tang, Jinhui
    Nie, Weizhi
    Su, Yuting
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2017, 36 (08) : 1699 - 1710
  • [39] Automated segmentation, classification, and tracking of cancer cell nuclei in time-lapse microscopy
    Chen, XW
    Zhou, XB
    Wong, STC
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2006, 53 (04) : 762 - 766
  • [40] Cell segmentation for division rate estimation in computerized video time-lapse microscopy
    He, Weijun
    Wang, Xiaoxu
    Metaxas, Dimitris
    Mathew, Robin
    White, Eileen
    MULTIMODAL BIOMEDICAL IMAGING II, 2007, 6431