Synthtic OCT Data for image processing performance testing
The use of synthetic images is needed for testing the performance of image processing methods in order to establish a ground truth to test performance metrics. However, these synthetic images do not represent real applications. The aim of this paper is to build a mathematical model to obtain a synth...
| Autor principal: | |
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| Outros Autores: | , , , |
| Formato: | conferenceObject |
| Idioma: | eng |
| Publicado em: |
2011
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.2/1995 |
| País: | Portugal |
| Oai: | oai:repositorioaberto.uab.pt:10400.2/1995 |
| Resumo: | The use of synthetic images is needed for testing the performance of image processing methods in order to establish a ground truth to test performance metrics. However, these synthetic images do not represent real applications. The aim of this paper is to build a mathematical model to obtain a synthetic noise-free image mimicking a real Optical Coherence Tomography (OCT) B-scan or volume from the human retina, in order to establish a ground truth for filtering performance metrics in this context. Moreover we also suggest a method to add speckle noise to this image based on the speckle noise of the given OCT volume. In this way we establish a replicable method to obtain a ground truth for image processing performance metrics that actually mimics a real case. |
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