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Traumatic and degenerative shoulder pathologies of which treatment strategy and success depends on correct diagnosis are more commonly encountered at the present time. The aim of this study is to help clinicians by using computer based decision support systems to diagnose correctly the degenerative and traumatic conditions of shoulder from MR images which is not an easy task in practice. Image patches...
Recent HMM-based approaches to handwritten word spotting require large amounts of learning samples and mostly rely on a prior segmentation of the document. We propose to use Bag-of-Features HMMs in a patch-based segmentation-free framework that are estimated by a single sample. Bag-of-Features HMMs use statistics of local image feature representatives. Therefore they can be considered as a variant...
Color variation in medical images degrades the classification performance of computer aided diagnosis systems. Traditionally, color segmentation algorithms mitigate this variability and improve performance. However, consistent and robust segmentation remains an open research problem. In this study, we avoid the tenuous phase of color segmentation by adapting a bag-of-features approach using scale...
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