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Automated MS-Lesion Segmentation by K-Nearest Neighbor Classification
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This paper proposes a new method for fully automated multiple sclerosis (MS) lesion segmentation in cranial magnetic resonance (MR) imaging. The algorithm uses the T1-weighted and the fluid attenuation inversion recovery scans. It is based the K-Nearest [...]

Auto-kNN: Brain Tissue Segmentation using Automatically Trained k-Nearest-Neighbor Classification
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In this paper we applied one of our regularly used processing pipelines for fully automated brain tissue segmentation. Brain tissue was segmented in cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM). Our algorithms for skull stripping, tissue [...]


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