Figure 7 - uploaded by Iván Gómez-Conde
Content may be subject to copyright.
Source publication
This paper describes a novel software algorithm, called constrained Sequential Monte Carlo (SMC) clusters, for tracking a large collection of individual cells from intra-vital two-photon microscopy image sequences. We show how our method and software tool, implemented in python, is useful for quantifying the motility of T and B lymphocytes involved...
Similar publications
This paper describes a novel software algorithm, called constrained Sequential Monte Carlo (SMC) clusters, for tracking a large collection of individual cells from intra-vital two-photon microscopy image sequences. We show how our method and software tool, implemented in python, is useful for quantifying the motility of T and B lymphocytes involved...
A python based software package that implements Sequential Monte Carlo (SMC) tracking is used for extracting dynamical information
of a large collection of individual cells from two-photon microscopy image sequences.We show how our software tool is useful
for quantifying the motility of B cells involved in immune response and for validating computa...
Citations
... What is typical for group formations is that they maintain certain patterns of motion. Some typical examples are: formations of aircrafts and ships, respectively , for air traffic control, sea, harbor or land surveillance [45,124] , flocks of bird migration trajectories for ecological purposes , tracking groups of cells [38,107,149,127] (for in vitro purposes , stem cells, cardiovascular treatment and other medical diagnostics ), a group of robots (for industrial tasks), a group of football players [152] in sport videos, convoys of vehicles and groups of pedestrians for traffic management [3]. Within this broad range of problems, one can distinguish two main classes: (1) tracking of multiple groups with only a few components per group, which is called small groups tracking, and (2) groups with a relatively large number of constituents whose individual members cannot be easily distinguished, termed large groups. ...
This work presents the current state-of-the-art in techniques for tracking a number of objects moving in a coordinated and interacting fashion. Groups are structured objects characterized with particular motion patterns. The group can be comprised of a small number of interacting objects (e.g. pedestrians, sport players, convoy of cars) or of hundreds or thousands of components such as crowds of people. The group object tracking is closely linked with extended object tracking but at the same time has particular features which differentiate it from extended objects. Extended objects, such as in maritime surveillance, are characterized by their kinematic states and their size or volume. Both group and extended objects give rise to a varying number of measurements and require trajectory maintenance. An emphasis is given here to sequential Monte Carlo (SMC) methods and their variants. Methods for small groups and for large groups are presented, including Markov Chain Monte Carlo (MCMC) methods, the random matrices approach and Random Finite Set Statistics methods. Efficient real-time implementations are discussed which are able to deal with the high dimensionality and provide high accuracy. Future trends and avenues are traced.
Bio-imaging techniques have recently gotten a lot of attention since they have enabled in-vivo imaging. They are expected to contribute to drug discovery, understanding of disease mechanisms etc. However, data retrieved by bioimaging techniques have been increasing in volume, and it is not anymore feasible to analyze it manually. Therefore automatic extraction of characteristic of a huge amount of data have become important. Moreover, quantitative analysis methods are required for statistical reliability. In this paper we introduce a method for the analysis of a sequence of bone tissue images taken by a two-photon microscope to quantify blood permeability of bone marrow. This method segments the input image sequence to blood vessel, bone marrow and bone regions by graph cuts which we extended according to the images. Permeability is quantified by the intensity of the segmentation result. We also confirm that our method shows that quantification tendency is similar to ground truth data made by an expert.
The Instituto Gulbenkian de Ciência (IGC)
is an international biomedical research
and graduate training Institute,
founded and supported by the
Calouste Gulbenkian Foundation,
in Portugal.
Historically, several in vitro/ex vivo microscopy imaging techniques have been used to study cellular interactions within the uterus and the placenta. As these experimental methods have revealed compelling facts about the biologic phenomena of cell-cell contacts in these organs, they cannot be used to study complex dynamic behavior of living cells inside their physiologic environment. For this, recent advances in intravital imaging techniques, together with two-photon microscopy, offer an exciting opportunity to study such dynamic immunologic processes at the cellular level in the complex uterine and placental tissues. In this article, we review experimental imaging techniques that have been used for studying the uterus and placenta. In particular, we describe the advantages of intravital techniques and discuss novel procedures that can be used in reproductive immunology. We also describe several technical details involved in image sequence post-processing required to extract useful data. Finally, we conclude by discussing how the reproductive immunology field may benefit from the broad use of these intravital techniques.
