In silico modeling of cancer cell dissemination and metastasis.

Metastasis is the main cause of cancer-related death. It is surprising then that the exact nature of metastasis-the process by which cancer cells leave the primary tumor to reach distant organs, and resume proliferation-is not fully understood. Moreover, the different conditions under which the immune system can either promote or suppress metastasis are only now beginning to be uncovered.

Selection of Mesenchymal-Like Metastatic Cells in Primary Tumors - An in silico Investigation.

In order to metastasize, cancer cells must undergo phenotypic transition from an anchorage-dependent form to a motile form via a process referred to as epithelial to mesenchymal transition. It is currently unclear whether metastatic cells emerge late during tumor progression by successive accumulation of mutations, or whether they derive from distinct cell populations already present during the early stages of tumorigenesis. Similarly, the selective pressures that drive metastasis are poorly understood.

Systems immunology: a survey of modeling formalisms, applications and simulation tools.

Immunological studies frequently analyze individual components (e.g., signaling pathways) of immune systems in a reductionist manner.

Streaming level set algorithm for 3D segmentation of confocal microscopy images.

We present a high performance variant of the popular geodesic active contours which are used for splitting cell clusters in microscopy images. Previously, we implemented a linear pipelined version that incorporates as many cues as possible into developing a suitable level-set speed function so that an evolving contour exactly segments a cell/nuclei blob. We use image gradients, distance maps, multiple channel information and a shape model to drive the evolution.

Detection of spatially correlated objects in 3D images using appearance models and coupled active contours.

We consider the problem of segmenting 3D images that contain a dense collection of spatially correlated objects, such as fluorescent labeled cells in tissue. Our approach involves an initial modeling phase followed by a data-fitting segmentation phase. In the first phase, cell shape (membrane bound) is modeled implicitly using a parametric distribution of correlation function estimates.

Computing shortest cycles on discrete surfaces for acurate topological modifications of medical image isosurfaces.

Topological control over discrete isosurface is of primordial interest in medical applications, especially discrete model building for active contours. Previous attempts showed that the key point in acurately modifying topology was computation of shortest cycles on the surface of interest. This paper generalizes the shortest path algorithm to compute shortest cycles in a given homotopy class on a discrete surface with arbitrary topology.