Coronary Artery Tracking in 3D Cardiac CT Images Using Local Morphological Reconstruction Operators

Automatic segmentation and tracking of the coronary artery tree from Cardiac Multislice-CT images is an important goal to improve the diagnosis and treatment of coronary artery disease. This paper presents a semi-automatic algorithm (one input point per vessel) based on morphological grayscale local reconstructions in 3D images devoted to the extraction of the coronary artery tree. The algorithm has been evaluated in the framework of the Coronary Artery Tracking Challenge 2008 [1], obtaining consistent results in overlapping measurements (a mean of 70% of the vessel well tracked). Poor results in accuracy measurements suggest that future work should refine the centerline extraction. The algorithm can be efficiently implemented and its general strategy can be easily extrapolated to a completely automated centerline extraction or to a user interactive vessel extractio

Towards a digital model of zebrafish embryogenesis. Integration of Cell Tracking and Gene Expression Quantification

We elaborate on a general framework composed of a set of computational tools to accurately quantificate cellular position and gene expression levels throughout early zebrafish embryogenesis captured over a time-lapse series of in vivo 3D images. Our modeling strategy involves nuclei detection, cell geometries extraction, automatic gene levels quantification and cell tracking to reconstruct cell trajectories and lineage tree which describe the animal development. Each cell in the embryo is then precisely described at each given time t by a vector composed of the cell 3D spatial coordinates (x; y; z) along with its gene expression level g. This comprehensive description of the embryo development is used to assess the general connection between genetic expression and cell movement. We also investigate genetic expression propagation between a cell and its progeny in the lineage tree. More to the point, this paper focuses on the evolution of the expression pattern of transcriptional factor goosecoid (gsc) through the gastrulation process between 6 and 9 hours post fertilization (hpf

Spatio-temporal filtering with morphological operators for robust cell migration estimation in "in-vivo" images

The understanding of the embryogenesis in living systems requires reliable quantitative analysis of the cell migration throughout all the stages of development. This is a major challenge of the "in-toto" reconstruction based on different modalities of "in-vivo" imaging techniques -spatio-temporal resolution and image artifacts and noise. Several methods for cell tracking are available, but expensive manual interaction -time and human resources- is always required to enforce coherence. Because of this limitation it is necessary to restrict the experiments or assume an uncontrolled error rate. Is it possible to obtain automated reliable measurements of migration? can we provide a seed for biologists to complete cell lineages efficiently? We propose a filtering technique that considers trajectories as spatio-temporal connected structures that prunes out those that might introduce noise and false positives by using multi-dimensional morphological operators

Image Processing Challenges in the Creation of Spatiotemporal Gene Expression Atlases of Developing Embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field

An Automatic Quantification and Registration Strategy to Create a Gene Expression Atlas of Zebrafish Embryogenesis

In order to properly understand and model the gene regulatory networks in animals development, it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains. In this paper, we propose a complete computational framework to fulfill this task and create a 3D Atlas of the early zebrafish embryogenesis annotated with both the cellular localizations and the level of expression of different genes at different developmental stages. The strategy to construct such an Atlas is described here with the expression pattern of 5 different genes at 6 hours of development post fertilization

3D + t Morphological Processing: Applications to Embryogenesis Image Analysis

We propose to directly process 3D + t image sequences with mathematical morphology operators, using a new classi?cation of the 3D+t structuring elements. Several methods (?ltering, tracking, segmentation) dedicated to the analysis of 3D + t datasets of zebra?sh embryogenesis are introduced and validated through a synthetic dataset. Then, we illustrate the application of these methods to the analysis of datasets of zebra?sh early development acquired with various microscopy techniques. This processing paradigm produces spatio-temporal coherent results as it bene?ts from the intrinsic redundancy of the temporal dimension, and minimizes the needs for human intervention in semi-automatic algorithms

Robust Iris Segmentation on Uncalibrated Noisy Images Using Mathematical Morphology

International audienceThis paper proposes a new approach for fast iris segmentation that relies on the closed nested structures of iris anatomy (the sclera is brighter than the iris, and the iris is brighter than the pupil) and on its polar symmetry. The described method applies mathematical morphology for polar/radial-invariant image filtering and for circular segmentation using shortest paths from generalized grey-level distances. The proposed algorithm obtained good results on the NICE-I contest and showed a very robust behavior, especially when dealing with half-closed eyes, different skin colours/illumination or subjects wearing glasses. © 2009 Elsevier B.V. All rights reserved

Counting Malaria parasites with a two-stage EM based algorithm using crowdsourced data

Malaria eradication of the worldwide is currently one of the main WHO’s global goals. In this work, we focus on the use of human-machine interaction strategies for lowcost fast reliable malaria diagnostic based on a crowdsourced approach. The addressed technical problem consists in detecting spots in images even under very harsh conditions when positive objects are very similar to some artifacts. The clicks or tags delivered by several annotators labeling an image are modeled as a robust finite mixture, and techniques based on the Expectation-Maximization (EM) algorithm are proposed for accurately counting malaria parasites on thick blood smears obtained by microscopic Giemsa-stained techniques. This approach outperforms other traditional methods as it is shown through experimentation with real data.Peer ReviewedPostprint (published version

Counting Malaria parasites with a two-stage EM based algorithm using crowdsourced data

Malaria eradication of the worldwide is currently one of the main WHO’s global goals. In this work, we focus on the use of human-machine interaction strategies for lowcost fast reliable malaria diagnostic based on a crowdsourced approach. The addressed technical problem consists in detecting spots in images even under very harsh conditions when positive objects are very similar to some artifacts. The clicks or tags delivered by several annotators labeling an image are modeled as a robust finite mixture, and techniques based on the Expectation-Maximization (EM) algorithm are proposed for accurately counting malaria parasites on thick blood smears obtained by microscopic Giemsa-stained techniques. This approach outperforms other traditional methods as it is shown through experimentation with real data.Peer Reviewe

TRIP (Travel Remote Infomation Platform) - a platform for monitoring traveler's health

Most of the studies reporting symptoms during the travel are done retrospectively (1),(2), increasing the odds of recall bias. Moreover, there is no information about the percentage of travelers that suffer mild or no symptoms during their trips because they never attend to a clinic afterwards. A IM The main aim of the study is to detect incidence of symptoms real-time amongst travelers visiting tropical and subtropical countries. Also, comparing symptoms between travelers taking or not malaria chemoprophylaxis and other demographic variables