Image Cytometry: Protocols for 2D and 3D Quantification in Microscopic Images

被引:41
|
作者
Chieco, Pasquale [1 ]
Jonker, Ard [2 ]
De Boer, Bouke A. [3 ]
Ruijter, Jan M. [3 ]
Van Noorden, Cornelis J. F. [2 ]
机构
[1] S Orsola Malpighi Univ Hosp, Ctr Appl Biomed Res, I-40138 Bologna, Italy
[2] Univ Amsterdam, Acad Med Ctr, Dept Cell Biol & Histol, NL-1105 AZ Amsterdam, Netherlands
[3] Univ Amsterdam, Acad Med Ctr, Dept Anat Embryol & Physiol, NL-1105 AZ Amsterdam, Netherlands
关键词
IN-SITU HYBRIDIZATION; DEVELOPING MOUSE HEART; GENE-EXPRESSION; QUANTITATIVE AUTORADIOGRAPHY; SCANNING MICRODENSITOMETRY; GLUTAMATE-DEHYDROGENASE; SECTION THICKNESS; CELL-DIVISION; DNA; TISSUE;
D O I
10.1016/j.proghi.2012.09.001
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Microscopy-based imaging is booming and the need for tools to retrieve quantitative data from images is urgent. This book provides simple but reliable tools to generate valid quantitative gene expression data, at the. mRNA, protein and activity level, from microscopic images in relation to structures in cells, tissues and organs in 2D and 3D. Volumes, areas, lengths and numbers of cells and tissues can be calculated and related to these gene expression data while preserving the 2D and 3D morphology. Image cytometry thus provides a comprehensive toolkit to study molecular processes and structural changes at the level of cells and tissues. (C) 2012 Elsevier GmbH. All rights reserved.
引用
收藏
页码:211 / 333
页数:123
相关论文
共 50 条
  • [1] Image cytometry for 2D and 3D quantification in microscopic images
    Van Noorden, Cornelis
    [J]. FASEB JOURNAL, 2014, 28 (01):
  • [2] Image Projection Network: 3D to 2D Image Segmentation in OCTA Images
    Li, Mingchao
    Chen, Yerui
    Ji, Zexuan
    Xie, Keren
    Yuan, Songtao
    Chen, Qiang
    Li, Shuo
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2020, 39 (11) : 3343 - 3354
  • [3] 3D IMAGES WITH 2D FOOTPRINT
    Ferre Ferri, Enrique
    [J]. REVISTA SONDA-INVESTIGACION Y DOCENCIA EN ARTES Y LETRAS, 2020, (09): : 73 - 82
  • [4] SHAPR predicts 3D cell shapes from 2D microscopic images
    Waibel, Dominik J. E.
    Kiermeyer, Niklas
    Atwell, Scott
    Sadafi, Ario
    Meier, Matthias
    Marr, Carsten
    [J]. ISCIENCE, 2022, 25 (11)
  • [5] Image scanners: 2D and 3D
    Handley, R.
    [J]. Advanced Imaging, 2001, 16 (07) : 28 - 33
  • [6] 2D and 3D image processing
    2D- und 3D-Bildverarbeitung
    [J]. 2001, Walter de Gruyter GmbH (43):
  • [7] Quantification of Asphalt Mixture Interlocking Utilizing 2D and 3D Image Processing
    Polaczyk, Pawel
    Ma, Yuetan
    Jarrar, Zaher
    Jiang, Xi
    Xiao, Rui
    Huang, Baoshan
    [J]. JOURNAL OF MATERIALS IN CIVIL ENGINEERING, 2023, 35 (01)
  • [8] Development of image processing techniques of 2D ultrasound images for 3D reconstruction
    Gaughan, S. L.
    Doyle, B. J.
    McGloughlin, T. M.
    [J]. IRISH JOURNAL OF MEDICAL SCIENCE, 2012, 181 : 44 - 44
  • [9] Delineating Trees in Noisy 2D Images and 3D Image-Stacks
    Gonzalez, German
    Tueretken, Engin
    Fleuret, Francois
    Fua, Pascal
    [J]. 2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2010, : 2799 - 2806
  • [10] CONVERSION OF 2D STEGANO IMAGES INTO A 3D STEREO IMAGE USING RANSAC
    Shrikalaa, M.
    Mathivanan, P.
    Jasmine, J. S. Leena
    [J]. 2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES (ICT 2013), 2013, : 686 - 690