Classification of Breast Lesions in Ultrasonography Using Sparse Logistic Regression and Morphology-based Texture Features

Nemat, H., Fehri, H., Ahmadinejad, N. et al. (2 more authors) (2018) Classification of Breast Lesions in Ultrasonography Using Sparse Logistic Regression and Morphology-based Texture Features. Medical Physics. ISSN 0094-2405

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 Wiley. This is the peer reviewed version of the following article: Nemat, H. , Fehri, H. , Ahmadinejad, N. , Frangi, A. F. and Gooya, A. (2018), Classification of breast lesions in ultrasonography using sparse logistic regression and morphology‐based texture features. Med. Phys, which has been published in final form at https://doi.org/10.1002/mp.13082. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Keywords: Classification; computer-aided diagnosis; logistic regression; segmentation; ultrasound images
Dates:
  • Published (online): 5 July 2018
  • Accepted: 29 April 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
Funding Information:
FunderGrant number
EUROPEAN COMMISSION - FP6/FP7BALMORAL - 625745
Depositing User: Symplectic Sheffield
Date Deposited: 25 Jul 2018 11:16
Last Modified: 05 Jul 2019 00:42
Published Version: https://doi.org/10.1002/mp.13082
Status: Published online
Publisher: Wiley
Refereed: Yes
Identification Number: https://doi.org/10.1002/mp.13082
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