Natalia Irishina

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In this paper we propose and analyse a novel shape-reconstruction technique for the early detection of breast cancer from microwave data, which is based on a level-set technique. The shape-based approach offers several advantages compared to more traditional pixel-based approaches, as, for example, well-defined boundaries and the incorporation of an(More)
We present a level-set based technique to recover key characteristics of a defect or crack (e.g. location, length and shape) in a two-dimensional material from boundary electrical measurements. The key feature of this work is to extend the usual level-set technique for modeling volumetric objects to very thin objects. Two level-set functions are employed:(More)
In this paper, we propose and analyze a novel shape reconstruction technique for the early detection of breast cancer from microwave data, which is based on a level-set technique. The shape-based approach offers several advantages compared to more traditional pixel-based approaches when targeting the reconstruction of key characteristics of a hidden tumor(More)
In this paper we investigate the performance of a shape-reconstruction technique as tested on the 'Marseille data'. This approach, which is based on a level set technique, offers several advantages compared to other approaches, as for example well-defined boundaries and the incorporation of an intrinsic regularization in the form of a priori assumptions(More)
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