Correction of mosaicking artifacts in multimodal images caused by uneven illumination. (June 2017) - Chernavskaia, Olga; Guo, Shuxia; Meyer, Tobias; Vogler, Nadine; Akimov, Denis; Heuke, Sandro; Heintzmann, Rainer; Bocklitz, Thomas; Popp, Jürgen
Abstract : Recent advances in nonlinear multimodal imaging, eg, the combination of coherent anti‐Stokes Raman scattering, 2‐photon excited autofluorescence, and second‐harmonic generation, have shown the great potential of this imaging technique for medical diagnostics. To extract reliable diagnostic information from these multimodal images, a complex image‐processing pipeline is necessary. A major part of this image‐processing pipeline is the elimination of the mosaicking artifact caused by an uneven illumination within the images. While this problem is well known in image processing of photographic images and methods to solve it were developed, their direct application to multimodal images does not yield satisfactory results. This fact results from the nonlinearity of the measurement modalities and characteristics of the multimodal images itself. In this contribution, different approaches to correct the mosaicking are considered and adapted to multimodal images. In this tutorial article, an investigation and comparative analysis of correction methods were performed, and practical recommendations for the application of different methods are given. The results of this paper can be applied to the development of complete or partial automatic software for medical diagnostics using nonlinear multimodal imaging techniques. Abstract : Nonlinear multicontrast microscopy or how it is often called multimodal imaging features molecular contrast, because it is the combination of coherent anti‐Stokes Raman scattering, second harmonic generation, and two photon–excited fluorescence. The application of this techniques for imaging of biological tissue is straight forward, which is the reason to investigate tissue diagnostics based on multimodal imaging. To do so, multimodal imaging needs to be combined with image analysis methods. To perform such an image analysis of the multimodal images in a reliable and robust manner, the images must be corrected for disturbing effects. One of the severest disturbing effects is the vignetting or mosaicking due to an uneven illumination. Chernavskaia et al introduce frequency and spatial domain methods for the correction of this artifacts based on an uneven illumination. The correction methods are compared in terms of computational complexity, adaption properties, and their robustness. Additionally, different spatial domain methods are compared. The article gives a guideline to choose a well‐performing correction. Nevertheless, none of the studied methods for the uneven illumination correction is always superior, which raises the question of a quantitative marker for the correction quality to decide, which correction is best to be applied.