Pathology Growth Model Based on Particles

Sierra, Raimundo; Bajka, Michael; Székely, Gábor

doi:10.1007/978-3-540-39899-8_4

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…The model described in the preceding sections was tested with a finite element volumetric mesh of an early development stage of a uterine polyp model presented in [10]. A few interior elements in the structure's head were picked and marked as actively dividing cells, which will be continuously secreting angiogenic growth factors and regulating the endothelial response.…”

Section: Resultsmentioning

confidence: 99%

Simulating Vascular Systems in Arbitrary Anatomies

Szczerba

Székely

2005

Lecture Notes in Computer Science

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Abstract. Better physiological understanding of principles regulating vascular formation and growth is mandatory to their efficient modeling for the purpose of physiologically oriented medical applications like training simulation or preoperative planning. We have already reported on the implementation of a visually oriented modeling framework allowing to study various physiological aspects of the vascular systems on a macroscopic scale. In this work we describe our progress in this field including (i) extension of the presented model to three dimensions, (ii) addition of established mathematical approaches to modeling angiogenesis and (iii) embedding the structures in arbitrary anatomical elements represented by finite element meshes.

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Section: Resultsmentioning

confidence: 99%

Simulating Vascular Systems in Arbitrary Anatomies

Szczerba

Székely

2005

Lecture Notes in Computer Science

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“…Finally, the particles positions are optimized to build a regular distribution over both the inner and surface domain. Therefore, the particles are rearranged based on the distance to their neighbors, similar to the method reported in the particle based tumor growth model [11]. The particles repulse or attract each other depending on an interaction profile function that relates the inter-particle distance to a force amplitude.…”

Section: Optimal 3d Mesh Generationmentioning

confidence: 99%

Coherent Scene Generation for Surgical Simulators

et al. 2004

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The idea of using computer-based surgical simulators for training of prospective surgeons has been a topic of research for more than a decade. However, surgical simulation is still far from being included into the medical curriculum. Still open questions are the level of simulation realism which is needed for effective learning, the identification of surgical skill components which are to be trained, as well as the validation of the training effect. We are striving to address these problems with a new generation of highly realistic simulators. A key element of realism is the variable training scene, reflecting differences in individual patients. In this paper we describe the complete generation process of these case-by-case scenarios.

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“…Particle System Finally, a particle-based growth model was developed [7]. Different types of particles are introduced (healthy tissue, pathology and surface).…”

Section: Pathology Generation Strategiesmentioning

confidence: 99%

Evaluation of different pathology generation strategies for surgical training simulators

Sierra

Bajka

Székely

2003

International Congress Series

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During the last few years several surgical training simulators have been proposed. One of the main advantages of these simulators is the ability to provide riskless training on a wide range of different cases in a compressed period of time. Therefore the generation of variable surgical scenes is a crucial component of a simulator. This paper compares three different approaches for the generation of pathologies specifically suited for surgical training simulators. The generated models can be embedded in the healthy organ model to challenge the trainee with a new case in every training.

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Pathology Growth Model Based on Particles

Cited by 4 publications

References 10 publications

Simulating Vascular Systems in Arbitrary Anatomies

Simulating Vascular Systems in Arbitrary Anatomies

Coherent Scene Generation for Surgical Simulators

Evaluation of different pathology generation strategies for surgical training simulators

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