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A Bag of Features Approach for CEUS Liver Lesions Investigation | IEEE Conference Publication | IEEE Xplore
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A Bag of Features Approach for CEUS Liver Lesions Investigation


Abstract:

In this work a novel approach for CEUS based diagnosis is presented. We propose a spatial/image-based method using a parallel and hierarchical system architecture. As a f...Show More

Abstract:

In this work a novel approach for CEUS based diagnosis is presented. We propose a spatial/image-based method using a parallel and hierarchical system architecture. As a feature extraction stage, we propose the Bag of Features (BoF) algorithm which treats image features as a bag of visual words. It is followed by a multiclass SVM classifier trained separately for each phase of the ultrasound investigation. A soft voting scheme has been proposed for the information fusion of the individual phase classifiers. The preliminary evaluation shows promising qualitative results of our approach on samples of a newly introduced CEUS dataset. Using only 550 images, (5 liver lesions × 10 pictures/lesion × 11 patients) an average accuracy of 64% has been obtained for a leave-one patient-out procedure.
Date of Conference: 01-03 July 2019
Date Added to IEEE Xplore: 25 July 2019
ISBN Information:
Conference Location: Budapest, Hungary

References

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