Abstract
Image registration is increasingly being used to help radiologists when comparing temporal mammograms for lesion detection and classification. This paper evaluates the use of image and deformation features extracted from image registration results in order to detect abnormal cases with masses. Using a dataset of 264 mammographic images from 66 patients (33 normals and 33 with masses) results show that the use of a non-rigid registration method clearly improves detection results compared to no registration (AUC: 0.76 compared to 0.69). Moreover, feature combination using left and right breasts further improves the performance (AUC to 0.88) compared to single image features.
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Martí, R., Díez, Y., Oliver, A., Tortajada, M., Zwiggelaar, R., Lladó, X. (2014). Detecting Abnormal Mammographic Cases in Temporal Studies Using Image Registration Features. In: Fujita, H., Hara, T., Muramatsu, C. (eds) Breast Imaging. IWDM 2014. Lecture Notes in Computer Science, vol 8539. Springer, Cham. https://doi.org/10.1007/978-3-319-07887-8_85
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DOI: https://doi.org/10.1007/978-3-319-07887-8_85
Publisher Name: Springer, Cham
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