Digital Image Analysis of Cells: Applications in 2D, 3D and Time

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Pinidiyaarachchi, Amalka,1975-Uppsala universitet,Centrum för bildanalys (författare)

Digital Image Analysis of Cells : Applications in 2D, 3D and Time

BokEngelska2009

Förlag, utgivningsår, omfång ...

Uppsala :Universitetsbiblioteket,2009
57 s.
electronicrdacarrier

Nummerbeteckningar

LIBRIS-ID:oai:DiVA.org:uu-9541
ISBN:9789155473983
https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9541URI

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Språk:engelska
Sammanfattning på:engelska

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Ämneskategori:dok swepub-publicationtype

Serie

Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology,1651-6214 ;596

Anmärkningar

Light microscopes are essential research tools in biology and medicine. Cell and tissue staining methods have improved immensely over the years and microscopes are now equipped with digital image acquisition capabilities. The image data produced require development of specialized analysis methods. This thesis presents digital image analysis methods for cell image data in 2D, 3D and time sequences.Stem cells have the capability to differentiate into speciﬁc cell types. The mechanism behind differentiation can be studied by tracking cells over time. This thesis presents a combined segmentation and tracking algorithm for time sequence images of neural stem cells.The method handles splitting and merging of cells and the results are similar to those achieved by manual tracking.Methods for detecting and localizing signals from ﬂuorescence stained biomolecules are essential when studying how they function and interact. A study of Smad proteins, that serve as transcription factors by forming complexes and enter the cell nucleus, is included in the thesis. Confocal microscopy images of cell nuclei are delineated using gradient information, and Smad complexes are localized using a novel method for 3D signal detection. Thus, the localization of Smad complexes in relation to the nuclear membrane can be analyzed. A detailed comparison between the proposed and previous methods for detection of point-source signals is presented, showing that the proposed method has better resolving power and is more robust to noise.In this thesis, it is also shown how cell conﬂuence can be measured by classiﬁcation of wavelet based texture features. Monitoring cell conﬂuence is valuable for optimization of cell culture parameters and cell harvest. The results obtained agree with visual observations and provide an efﬁcient approach to monitor cell conﬂuence and detect necrosis.Quantitative measurements on cells are important in both cytology and histology. The color provided by Pap (Papanicolaou) staining increases the available image information. The thesis explores different color spaces of Pap smear images from thyroid nodules, with the aim of ﬁnding the representation that maximizes detection of malignancies using color information in addition to quantitative morphological parameters.The presented methods provide useful tools for cell image analysis, but they can of course also be used for other image analysis applications.

Ämnesord och genrebeteckningar

NATURVETENSKAP Data- och informationsvetenskap Datorseende och robotik hsv//swe
NATURAL SCIENCES Computer and Information Sciences Computer Vision and Robotics hsv//eng
Digital image analysis
microscopy
ﬂuorescent staining
watershed segmentation
sub-cellular localization
point-like signals
wavelets
cell conﬂuence
cytology
color spaces.
Image analysis
Bildanalys

Biuppslag (personer, institutioner, konferenser, titlar ...)

Wählby, Carolina,Assistant ProfessorUppsala universitet,Centrum för bildanalys (preses)
Bengtsson, Ewert,ProfessorUppsala universitet,Centrum för bildanalys (preses)
Lundervold, Arvid,ProfessorDepartment of Biomedicine and Molecular Imaging Center , University of Bergen (opponent)
Uppsala universitetCentrum för bildanalys (creator_code:org_t)

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Av författaren/redakt...: Pinidiyaarachchi ...; Wählby, Carolina ...; Bengtsson, Ewert ...; Lundervold, Arvi ...

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