field functions are derived via genetic programming (GP), an evolutionary computing process that evolves a population of functions. A fitness measure, based on the shape that emerges from the chemical-field-driven aggregation, determines which functions will be passed along to later generations. This paper describes the cell interactions of MPs and the GP-based method used to define the chemical field functions needed to produce user-specified shapes from simple aggregating primitives.

Manolya Eyiyurekli McCormick, PhD

I graduated summa cum laude from Isik University in Istanbul with a bachelor's degree in Computer Science and Engineering before moving to Philadelphia for attending graduate school. I received my M.S. degree in 2006 and PhD degree in 2012 from the Department of Computer Science at Drexel University. I was the recipient of George Hill Jr. Endowed Fellowship in 2008. My doctorate work received the Outstanding Graduate Student Research Award from Drexel University's Department of Computer Science in 2011.

Data Structures for Interactive High Resolution Level-Set Surface Editing

PUBLICATIONS

Interactive Freeform Editing Techniques for Large-Scale, Multiresolution Level Set Models

M. E. McCormick, PhD Thesis, Computer Science Department, Drexel University, 2012.

Abstratct:

This dissertation describes techniques and algorithms for interactive freeform editing of large-scale, multiresolution level set models. Algorithms are developed to map intuitive user interactions into level set speed functions producing specific, desired surface movements. Data structures for efficient representation of very high resolution volume datasets and associated algorithms for rapid access and processing of the information within the data structures are explained. A hierarchical, multiresolution representation of level set models that allows for rapid decomposition and reconstruction of the complete full-resolution model is created for an editing framework that allows level-of-detail editing.

The traditional level set method is enhanced with techniques to preserve high resolution surface details of evolving level set surfaces, which are utilized for geometric texture transfers between two level set models.

Abstratct:

This paper presents data structures that enable interactive editing of large-scale level-set surface models. The new approach utilizes spatial hashing to store a narrow band of voxels around the level-set interface, as well as a k-d tree to hold the model's display points that lie on the surface itself. This sparse representation of voxels and surface points lets us create and modify high resolution level-set models with modest memory requirements, while allowing fast data access/modifications and interactive graphics updates. The data structures also support out-of-the-box editing, i.e.~no bounding box limits the surface editing region, a restriction common when utilizing 3-D arrays. We formally define the level-set representation and demonstrate its interactive performance and scalability through manipulation of high-resolution level-set surface models.

M. Eyiyurekli and D. Breen

Proceedings of Graphics Interface, May 2011, pp.95-102.

Interactive Free-Form Level-Set Surface-Editing Operators

Abstratct:

We present a set of interactive, free-form editing operators for direct manipulation of level-set models. The mathematics, algorithms and techniques needed to implement numerous level-set modeling capabilities have been developed. The operators have been combined with an OpenGL interface and the VISPACK level-set library to create a preliminary interactive level-set modeling system. VISPACK’s narrow-band data structures have been extended to localize all computations and updates to optimize running time. We describe the level- set speed functions that implement the surface-editing operators. A level-set surface can be edited through a click-sketch-and-pull interface that allows a user to identify a point or Region-of-Influence (ROI) to be modified on the surface. The user may then pull a point or a curve within the ROI to produce a free-form surface manipulation. Additional operators include surface detailing, carving and smoothing, as well as a sketch-based technique that pulls the surface toward a profile curve.

M. Eyiyurekli and D. Breen

Computers & Graphics, Vol. 34 No. 5, 2010, pp. 621-638.

Editing Level-Set Models with Sketched Curves

Abstratct:

Level set models are deformable implicit surfaces where the deformation is controlled by a speed function in the level set partial differential equation (PDE). These models are widely used in computer graphics applications due to their implicit definition, low-level volumetric representation and the powerful numerical techniques used to produce the PDE-based deformation. We present a set of interactive sketch-based level-set surface editing operators. These operators allow a user to sketch curves above or on a level-set surface in order to edit the surface’s shape. Once the curves are sketched the surface interactively evolves to locally fit to the curves. A user may then modify the curves in order to refine the shape of the model. The mathematics, algorithms and techniques needed to implement numerous sketch-based level set modeling capabilities are described. The speed functions that produce the surface deformations within the context of solving the level-set PDE are detailed. Several examples are presented to demonstrate the flexibility and usefulness of the editing operators.

M. Eyiyurekli, C. Grimm and D. Breen

Proceedings of Eurographics/ACM Symposium on Sketch-Based Interfaces and Modeling, August 2009, pp. 45-52.

Localized Editing of Catmull-Rom Splines

Abstratct:

Catmull-Rom (C-R) splines offer many useful modeling properties, such as affine invariance, global smoothness, and local control. They are therefore of great interest to Computer Aided Design (CAD) users. C-R splines are easily evaluated and are a good choice for interactive applications because they interpolate their control points and therefore provide an intuitive way to represent and edit curves in these applications. We have developed an interactive free-form surface-editing framework that uses Catmull-Rom splines for sketch-based editing. Mouse strokes are translated into splines that are used to define free-form surface deformations. Direct control point manipulation is provided for the modification of the splines. Unfortunately, the definition of C-R splines dictates that moving one control point only affects a small, fixed portion of the curve. In order to provide greater flexibility, control and expressiveness, we have developed techniques that expand and generalize the result of modifying one C-R control point. The techniques allow the user to define the range and type of influence that manipulation of a single control point may produce on a C-R curve, providing a versatile and powerful localized curve editing capability.

M. Eyiyurekli and D. Breen

Computer-Aided Design and Applications, Vol. 6, No. 3, 2009, pp. 307-316.


Chemotaxis-based Sorting of Self-Organizing Heterotypic Agents

Abstratct:

Cell sorting is a fundamental phenomenon in morphogenesis, which is the process that leads to shape formation in living organisms. The sorting of heterotypic cell populations is produced by a variety of inter-cellular actions, e.g. differential chemotactic response, adhesion and motility. Via a process called chemotaxis, living cells respond to chemicals released by other cells into the environment. Each cell can respond to the stimulus by moving in the direction of the gradient of the cumulative chemical field detected at its surface. Inspired by the biological phenomena of chemotaxis and cell sorting in heterotypic cell aggregates, we propose a chemotaxis-based algorithm for the sorting of self-organizing heterotypic agents. In our algorithm two types of agents are initially randomly placed in a toroidal environment. Agents emit a chemical signal and interact with nearby agents. Given the appropriate parameters, the two kinds of agents self-organize into a complex aggregate consisting of a group of one type of agents surrounded by agents of the second type. This paper describes the chemotaxis-based sorting algorithm, the behaviors of our self-organizing heterotypic agents, evaluation of the final aggregates and parametric studies of the results.

M. Eyiyurekli, L. Bai, P. Lelkes and D. Breen

Proceedings of 25th ACM Symposium on Applied Computing, March 2010, pp. 1315-1322.



An Emergent System for Self-Aligning and Self-Organizing Shape Primitives

Abstratct:

Motivated by the natural phenomenon of living cells self-organizing into specific shapes and structures, we present an emergent system that utilizes evolutionary computing methods for designing and simulating self-aligning and self-organizing shape primitives. Given the complexity of the emergent behavior, genetic programming is employed to control the evolution of our emergent system. The system has two levels of description. At the macroscopic level, a user-specified, pre-defined shape is given as input to the system. The system outputs local interaction rules that direct morphogenetic primitives (MP) to aggregate into the shape. At the microscopic level, MPs follow interaction rules based only on local interactions. All MPs are identical and do not know the final shape to be formed. The aggregate is then evaluated at the macroscopic level for its similarity to the user-defined shape. In this paper, we present (1) an emergent system that discovers local interaction rules that direct MPs to form user-defined shapes, (2) the simulation system that implements these rules and causes MPs to self-align and self-organize into a user-defined shape, and (3) the robustness and scalability qualities of the overall approach.


L. Bai, M. Eyiyurekli and D. Breen

Proceedings of Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems, October 2008, pp. 445-454.




A Computational Model of Chemotaxis-based Cell Aggregation

Abstratct:

We present a computational model that successfully captures the cell behaviors that play important roles in 2-D cell aggregation. A virtual cell in our model is designed as an independent, discrete unit with a set of parameters and actions. Each cell is defined by its location, size, rates of chemoattractant emission and response, age, life cycle stage, proliferation rate and number of attached cells. All cells are capable of emitting and sensing a chemoattractant chemical, moving, attaching to other cells, dividing, aging and dying. We validated and fine-tuned our in silico model by comparing simulated 24-h aggregation experiments with data derived from in vitro experiments using PC12 pheochromocytoma cells. Quantitative comparisons of the aggregate size distributions from the two experiments are produced using the Earth Mover's Distance (EMD) metric. We compared the two size distributions produced after 24 h of in vitro cell aggregation and the corresponding computer simulated process. Iteratively modifying the model's parameter values and measuring the difference between the in silico and in vitro results allow us to determine the optimal values that produce simulated aggregation outcomes closely matched to the PC12 experiments. Simulation results demonstrate the ability of the model to recreate large-scale aggregation behaviors seen in live cell experiments.



M. Eyiyurekli, P. Manley, P. Lelkes and D. Breen

BioSystems, Vol. 93, No. 3, pp. 226-239, September 2008.





Automated Shape Composition Based on Cell Biology and Distributed Genetic Programming

Abstratct:

Motivated by the ability of living cells to form specific shapes and structures, we present a computational approach using distributed genetic programming to discover cell-cell interaction rules for automated shape composition. The key concept is to evolve local rules that direct virtual cells to produce a self-organizing behavior that leads to the formation of a macroscopic, user-defined shape. The interactions of the virtual cells, called Morphogenic Primitives (MPs), are based on chemotaxis-driven aggregation behaviors exhibited by actual living cells. Cells emit a chemical into their environment. Each cell responds to the stimulus by moving in the direction of the gradient of the cumulative chemical field detected at its surface. MPs, though, do not attempt to completely mimic the behavior of real cells. The chemical fields are explicitly defined as mathematical functions and are not necessarily physically accurate. The functions are derived via a distributed genetic programming process. A fitness measure, based on the shape that emerges from the chemical-field-driven aggregation, determines which functions will be passed along to later generations. This paper describes the cell interactions of MPs and a distributed genetic programming method to discover the chemical fields needed to produce macroscopic shapes from simple aggregating primitives.




L. Bai, M. Eyiyurekli and D. Breen

Proceedings of Genetic and Evolutionary Computation Conference, July 2008, pp. 1179-1186.






Self-Organizing Primitives for Automated Shape Composition

Abstratct:

Motivated by the ability of living cells to form into specific shapes and structures, we present a new approach to shape modeling based on self-organizing primitives whose behaviors are derived via genetic programming. The key concept of our approach is that local interactions between the primitives direct them to come together into a macroscopic shape. The interactions of the primitives, called Morphogenic Primitives (MP), are based on the chemotaxis-driven aggregation behaviors exhibited by actual living cells. Here, cells emit a chemical into their environment. Each cell responds to the stimulus by moving in the direction of the gradient of the cumulative chemical field detected at its surface. MPs, though, do not attempt to completely mimic the behavior of real cells. The chemical fields are explicitly defined as mathematical functions and are not necessarily physically accurate. The explicit mathematical form of the chemical





L. Bai, M. Eyiyurekli and D. Breen

Proceedings of Shape Modeling International 2008 Conference, June 2008, pp. 147-154.







Simulation of Chemotaxis-based Sorting of Heterotypic Cell Populations

Abstratct:

Cell sorting is a fundamental process that is involved in early embryo development, tumerogenesis and morphogenesis. The sorting of heterotypic cell populations is produced by a variety of inter-cellular actions, e.g. differential adhesion and motility. We recently developed a software system that simulates chemotaxis-based cell aggregation in 2D. The model implemented within the system includes a variety of physiological cell behaviors, such as chemical diffusion/detection, motility, proliferation, adhesion and life cycle stages. In this paper we extend the model to simulate heterotypic cell sorting. This paper provides an overview of the chemotaxis-based aggregation model and describes the parameters and processes utilized to simulate the sorting of two different cell populations based on chemotactic interactions.




M. Eyiyurekli, P. Lelkes and D. Breen

Proceedings of IEEE / NIH BISTI Life Science Systems & Applications Workshop, November 2007, pp. 47-50.






A Computational System for Investigating Chemotaxis-Based Cell Aggregation

Abstratct:

We have developed a software system that simulates chemotaxis-based cell aggregation in 2D. The model implemented within the system consists of such cell behaviors as chemical diffusion/detection, motility, proliferation, adhesion and life cycle stages. Each virtual cell detects the state of the environment, and responds to the environment based on a pre-defined "program" and its own internal state. Cells are discrete units that are located on a grid, exist in discrete states (e.g. active or dying) and perform discrete tasks (e.g. divide and attach), but they also contain and are affected by continuous quantities (e.g. chemoattractant concentrations, gradients, age and velocities). This paper provides an overview of our chemotaxis-based aggregation model and details the algorithms required to perform chemotaxis-based cell aggregation simulation. A number of biological studies are being conducted with the system. They include fine-tuning the model parameters to reproduce in vitro PC12 cell aggregation experiments and parametric studies that demonstrate the effect that the model's components have on cell aggregation dynamics.





M. Eyiyurekli, P. Lelkes and D. Breen

Proceedings of European Conference on Artificial Life, September 2007, pp. 1034-1049.







Last Updated: 01/02/2013