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Cellular Image Classification

Kataloginformation Katalogdatensatz500243034 .

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Feldname	Details
Vorliegende Sprache	eng
ISBN	978-3-319-47628-5
Name	Xu, Xiang
Name	Wu, Xingkun
Name ANZEIGE DER KETTE	Wu, Xingkun
Name	Lin, Feng
T I T E L	Cellular Image Classification
Verlagsort	Cham
Verlag	Springer
Erscheinungsjahr	2017
Erscheinungsjahr	2017
Umfang	Online-Ressource (IX, 137 p. 60 illus, online resource)
Reihe	SpringerLink. Bücher
Titelhinweis	Druckausg.ISBN: 978-3-319-47628-5
Titelhinweis	Printed editionISBN: 978-3-319-47628-5
ISBN	ISBN 978-3-319-47629-2
Klassifikation	TTBM
	UYS
	TEC008000
	COM073000
	*92-02
	92C55
	92C99
	68U10
	621.382
	TK5102.9
	TA1637-1638
	TK7882.S65
Kurzbeschreibung	This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical tweezer applications, including selective cell pick-up, pairing, grouping or separation, as well as rotation of cell dimers and clusters. Both translational dragging force and rotational torque in the experiments are in good accordance with the theoretical model. With a simple all-fiber configuration, and low peak irradiation to targeted cells, instrumentation of this optical chuck technology will provide a powerful tool in the ANA-IIF laboratories. Chapters focus on the optical, mechanical and computing systems for the clinical trials. Computer programs for GUI and control of the optical tweezers are also discussed. to more discriminative local distance vector by searching for local neighbors of the local feature in the class-specific manifolds. Encoding and pooling the local distance vectors leads to salient image representation. Combined with the traditional coding methods, this method achieves higher classification accuracy. Then, a rotation invariant textural feature of Pairwise Local Ternary Patterns with Spatial Rotation Invariant (PLTP-SRI) is examined. It is invariant to image rotations, meanwhile it is robust to noise and weak illumination. By adding spatial pyramid structure, this method captures spatial layout information. While the proposed PLTP-SRI feature extracts local feature, the BoW framework builds a global image representation. It is reasonable to combine them together to achieve impressive classification performance, as the combi ...
2. Kurzbeschreibung	Introduction -- Fundamentals -- Optical Systems for Cellular Imaging -- Image Representation with Bag-of-Words -- Image Coding -- Encoding Image Features -- Defining Feature Space for Image Classification -- Conclusions and Perspectives
SWB-Titel-Idn	480955077
Signatur	Springer E-Book
Bemerkungen	Elektronischer Volltext - Campuslizenz
Elektronische Adresse	$uhttp://dx.doi.org/10.1007/978-3-319-47629-2
Internetseite / Link	Volltext
Siehe auch	Inhaltstext

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