Kiran Vaidhya

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We present a fully automated generative method for brain tumor segmentation in multi-modal magnetic resonance images. We base the method on the type of generative model often used for healthy brain tissues, where tissues are modeled by Gaussian mixture models combined with a spatial tissue prior. We extend the basic model with a tumor prior, which uses(More)
The work presented explores the use of denoising autoencoders (DAE) for brain lesion detection, segmentation and false positive reduction. Stacked denoising autoencoders (SDAE) were pre-trained using a large number of unlabeled patient volumes and fine tuned with patches drawn from a limited number of patients (n=20, 40, 65). The results show negligible(More)
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