3D time series analysis of cell shape using Laplacian approaches

Background: Fundamental cellular processes such as cell movement, division or food uptake critically depend on cells being able to change shape. Fast acquisition of three-dimensional image time series has now become possible, but we lack efficient tools for analysing shape deformations in order to understand the real three-dimensional nature of shape changes. Results: We present a framework for 3D+time cell shape analysis. The main contribution is three-fold: First, we develop a fast, automatic random walker method for cell segmentation. Second, a novel topology fixing method is proposed to fix segmented binary volumes without spherical topology. Third, we show that algorithms used for each individual step of the analysis pipeline (cell segmentation, topology fixing, spherical parameterization, and shape representation) are closely related to the Laplacian operator. The framework is applied to the shape analysis of neutrophil cells. Conclusions: The method we propose for cell segmentation is faster than the traditional random walker method or the level set method, and performs better on 3D time-series of neutrophil cells, which are comparatively noisy as stacks have to be acquired fast enough to account for cell motion. Our method for topology fixing outperforms the tools provided by SPHARM-MAT and SPHARM-PDM in terms of their successful fixing rates. The different tasks in the presented pipeline for 3D+time shape analysis of cells can be solved using Laplacian approaches, opening the possibility of eventually combining individual steps in order to speed up computations

Radiology

Radiology is the fastest developing field of medicine and these unprecedented advances have been mainly due to improving computer technology. Digital imaging is a technology whereby images are acquired in a computer format, so that they can be easily stored and recalled for display on any computer workstation. Digital image acquisition has been used in ultrasound, computed tomography (CT) and magnetic resonance imaging (MRI) from the start. The use of digital imaging in conventional X-rays, known as Computed Radiography, has only recently become possible. Supercomputers now provide the speed required to rapidly process digital image data, while terabyte level storage media allow digital archiving of both radiological images and data. Ultrasound, CT and MRI have also improved immensely as a result of faster computing, which allows shorter exam times, higher image resolution with improved quality and new exam techniques including large field and realtime imaging, noninvasive angiography and dynamic motion studies. Other recent advances in radiology include new contrast agents, Positron Emission Tomography (PET) scanning and novel interventional techniques.peer-reviewe

Extracting the hierarchical organization of complex systems

Extracting understanding from the growing ``sea'' of biological and socio-economic data is one of the most pressing scientific challenges facing us. Here, we introduce and validate an unsupervised method that is able to accurately extract the hierarchical organization of complex biological, social, and technological networks. We define an ensemble of hierarchically nested random graphs, which we use to validate the method. We then apply our method to real-world networks, including the air-transportation network, an electronic circuit, an email exchange network, and metabolic networks. We find that our method enables us to obtain an accurate multi-scale descriptions of a complex system.Comment: Figures in screen resolution. Version with full resolution figures available at http://amaral.chem-eng.northwestern.edu/Publications/Papers/sales-pardo-2007.pd