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Martínez-Más, José and Bueno-Crespo, Andrés and Khazendar, Shan and Remezal, Manuel and Martínez-Cendán, Juan-Pedro and Jassim, Sabah A. and Du, Hongbo and Al-Assam, Hisham and Bourne, Tom and Timmerman, Dirk (2019) Evaluation of machine learning methods with Fourier Transform features for classifying ovarian tumors based on ultrasound images. PloS ONE, 14 (7). pp. 1-14. ISSN 1932-6203
Khazendar, Shan and Sayasneh, Ahmad and Al-Assam, Hisham and Du, Hongbo and Kaijer, J. and Ferrara, L. and Timmerman, Dirk and Jassim, Sabah A. and Bourne, Tom (2015) Automated characterisation of ultrasound images of ovarian tumours: the diagnostic accuracy of a support vector machine and image processing with a local binary pattern operator. Facts, Views and Visions in ObGyn, 7 (16). pp. 7-15. ISSN 2032-0418
Khazendar, Shan and Farren, Jessica and Al-Assam, Hisham and Du, Hongbo and Sayasneh, Ahmed and Bourne, Tom and Jassim, Sabah A. (2015) Automatic Identification of Miscarriage Cases Supported by Decision Strength Using Ultrasound Images of the Gestational Sac. Annals of the BMVA, 2015 (5). pp. 1-16.
Al-karawi, Durgham and Landolfo, Chiara and Du, Hongbo and Al-Assam, Hisham and Sayasneh, Ahmad and Timmerman, Dirk and Bourne, Tom and Jassim, Sabah A. (2019) OC04.04 : A machine-learning algorithm to distinguish benign and malignant adnexal tumours from ultrasound images. In: 29th ISUOG Congress 2019., 12-16 October 2019, Berlin, Germany.
Al-karawi, D. and Landolfo, C. and Du, Hongbo and Al-Assam, Hisham and Sayasneh, A. and Timmerman, Dirk and Bourne, Tom and Jassim, Sabah A. (2019) Prospective clinical evaluation of texture‐based features analysis of ultrasound ovarian scans for distinguishing benign and malignant adnexal tumors. In: Fourth International IOTA Congress, April 18-19 2019, Leuven, Belgium.
