國立虎尾科技大學 |

Bioimage Data Analysis Workflows ‒ Advanced Components and Methods

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / edited by Kota Miura, Nataša Sladoje.
other author:	Miura, Kota.
Description:	X, 212 p. 265 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Cytology. -
Online resource:	https://doi.org/10.1007/978-3-030-76394-7
ISBN:	9783030763947

Bioimage Data Analysis Workflows ‒ Advanced Components and Methods
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods [electronic resource] /edited by Kota Miura, Nataša Sladoje. - 1st ed. 2022. - X, 212 p. 265 illus. in color.online resource. - Learning Materials in Biosciences,2509-6133. - Learning Materials in Biosciences,1.

Introduction -- Batch Processing Methods in ImageJ -- Python: Data Handling, Analysis and Plotting -- Building a Bioimage Analysis Workflow Using Deep Learning -- GPU-Accelerating ImageJ Macro Image Processing Workflows Using CLIJ -- How to Do the Deconstruction of Bioimage Analysis Workflows: A Case Study with SurfCut -- i.2.i. with the (Fruit) Fly: Quantifying Position Effect Variegation in Drosophila Melanogaster -- A MATLAB Pipeline for Spatiotemporal Quantification of Monolayer Cell Migration.

Open Access

This open access textbook aims at providing detailed explanations on how to design and construct image analysis workflows to successfully conduct bioimage analysis. Addressing the main challenges in image data analysis, where acquisition by powerful imaging devices results in very large amounts of collected image data, the book discusses techniques relying on batch and GPU programming, as well as on powerful deep learning-based algorithms. In addition, downstream data processing techniques are introduced, such as Python libraries for data organization, plotting, and visualizations. Finally, by studying the way individual unique ideas are implemented in the workflows, readers are carefully guided through how the parameters driving biological systems are revealed by analyzing image data. These studies include segmentation of plant tissue epidermis, analysis of the spatial pattern of the eye development in fruit flies, and the analysis of collective cell migration dynamics. The presented content extends the Bioimage Data Analysis Workflows textbook (Miura, Sladoje, 2020), published in this same series, with new contributions and advanced material, while preserving the well-appreciated pedagogical approach adopted and promoted during the training schools for bioimage analysis organized within NEUBIAS – the Network of European Bioimage Analysts. This textbook is intended for advanced students in various fields of the life sciences and biomedicine, as well as staff scientists and faculty members who conduct regular quantitative analyses of microscopy images.

ISBN: 9783030763947

Standard No.: 10.1007/978-3-030-76394-7doiSubjects--Topical Terms:

599554
Cytology.

LC Class. No.: QH573-671

Dewey Class. No.: 571.6

Bioimage Data Analysis Workflows ‒ Advanced Components and Methods
LDR:03539nam a22004215i 4500 001 1083682
003 DE-He213
005 20220928203751.0
007 cr nn 008mamaa
008 221228s2022 sz | s |||| 0|eng d
020 $a 9783030763947 $9 978-3-030-76394-7
024 7 $a 10.1007/978-3-030-76394-7 $2 doi
035 $a 978-3-030-76394-7
050 4 $a QH573-671
072 7 $a PSF $2 bicssc
072 7 $a SCI049000 $2 bisacsh
072 7 $a PSF $2 thema
082 0 4 $a 571.6 $2 23
245 1 0 $a Bioimage Data Analysis Workflows ‒ Advanced Components and Methods $h [electronic resource] / $c edited by Kota Miura, Nataša Sladoje.
250 $a 1st ed. 2022.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a X, 212 p. 265 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Learning Materials in Biosciences, $x 2509-6133
505 0 $a Introduction -- Batch Processing Methods in ImageJ -- Python: Data Handling, Analysis and Plotting -- Building a Bioimage Analysis Workflow Using Deep Learning -- GPU-Accelerating ImageJ Macro Image Processing Workflows Using CLIJ -- How to Do the Deconstruction of Bioimage Analysis Workflows: A Case Study with SurfCut -- i.2.i. with the (Fruit) Fly: Quantifying Position Effect Variegation in Drosophila Melanogaster -- A MATLAB Pipeline for Spatiotemporal Quantification of Monolayer Cell Migration.
506 0 $a Open Access
520 $a This open access textbook aims at providing detailed explanations on how to design and construct image analysis workflows to successfully conduct bioimage analysis. Addressing the main challenges in image data analysis, where acquisition by powerful imaging devices results in very large amounts of collected image data, the book discusses techniques relying on batch and GPU programming, as well as on powerful deep learning-based algorithms. In addition, downstream data processing techniques are introduced, such as Python libraries for data organization, plotting, and visualizations. Finally, by studying the way individual unique ideas are implemented in the workflows, readers are carefully guided through how the parameters driving biological systems are revealed by analyzing image data. These studies include segmentation of plant tissue epidermis, analysis of the spatial pattern of the eye development in fruit flies, and the analysis of collective cell migration dynamics. The presented content extends the Bioimage Data Analysis Workflows textbook (Miura, Sladoje, 2020), published in this same series, with new contributions and advanced material, while preserving the well-appreciated pedagogical approach adopted and promoted during the training schools for bioimage analysis organized within NEUBIAS – the Network of European Bioimage Analysts. This textbook is intended for advanced students in various fields of the life sciences and biomedicine, as well as staff scientists and faculty members who conduct regular quantitative analyses of microscopy images.
650 0 $a Cytology. $3 599554
650 0 $a Bioinformatics. $3 583857
650 0 $a Imaging systems in biology. $3 640661
650 1 4 $a Cell Biology. $3 593889
650 2 4 $a Computational and Systems Biology. $3 1365723
650 2 4 $a Biological Imaging. $3 1388121
700 1 $a Miura, Kota. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1313825
700 1 $a Sladoje, Nataša. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1313826
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030763930
776 0 8 $i Printed edition: $z 9783030763954
830 0 $a Learning Materials in Biosciences, $x 2509-6125 ; $v 1 $3 1269359
856 4 0 $u https://doi.org/10.1007/978-3-030-76394-7
912 $a ZDB-2-SBL
912 $a ZDB-2-SXB
912 $a ZDB-2-SOB
950 $a Biomedical and Life Sciences (SpringerNature-11642)
950 $a Biomedical and Life Sciences (R0) (SpringerNature-43708)