Additional methods to analyze computer tomography data for medical purposes and generatively produced technical components

0Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The result of a computer tomography (CT) record is an image layer stack, which can be applied for medical diagnostic purposes, as well for virtual 3D object representation (e.g. for a skull bone) depending on the used threshold values. Based on these representations, medical 3D objects could be easily produced by generative manufacturing processes. The additive manufacturing of individual implants is also based on the use of CT data for the representation of the remaining bone. This knowledge was further used for the evaluation of industrial CT data. For technical applications, the industrial computer tomography becomes more and more important. Compared with devices from the medical area, industrial CT devices have a significantly higher radiation power and a much higher resolution. Thus, these data are not only suitable for the reconstruction of a 3D model in the sense of reverse engineering, but also for the inspection of components of metal workpieces (density differences, cavities, joint connection). The known CT evaluation procedures from medical use have been qualified and further modified in the research group. The developed software solution allows the generation of free-form sections through a layer image stack e.g. to evaluate the quality of a soldered connection in a tube. This procedure is also suitable to detect and determine density differences and the detachment of individual layers of a generative produced component. The topic is illustrated by selected practical examples.

Cite

CITATION STYLE

APA

Sembdner, P., Holtzhausen, S., Schöne, C., & Stelzer, R. (2013). Additional methods to analyze computer tomography data for medical purposes and generatively produced technical components. In IFIP Advances in Information and Communication Technology (Vol. 411, pp. 221–229). Springer New York LLC. https://doi.org/10.1007/978-3-642-41329-2_23

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free