Classification of kidney and liver tissue using ultrasound backscatter data

Fereshteh Aalamifar; Hassan Rivaz; Juan J. Cerrolaza; James Jago; Nabile Safdar M.D.; Emad M. Boctor; Marius George Linguraru

doi:10.1117/12.2082300

17 March 2015 Classification of kidney and liver tissue using ultrasound backscatter data

Fereshteh Aalamifar, Hassan Rivaz, Juan J. Cerrolaza, James Jago, Nabile Safdar M.D., Emad M. Boctor, Marius George Linguraru

Author Affiliations +

Proceedings Volume 9419, Medical Imaging 2015: Ultrasonic Imaging and Tomography; 94190X (2015) https://doi.org/10.1117/12.2082300
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Ultrasound (US) tissue characterization provides valuable information for the initialization of automatic segmentation algorithms, and can further provide complementary information for diagnosis of pathologies. US tissue characterization is challenging due to the presence of various types of image artifacts and dependence on the sonographer’s skills. One way of overcoming this challenge is by characterizing images based on the distribution of the backscatter data derived from the interaction between US waves and tissue. The goal of this work is to classify liver versus kidney tissue in 3D volumetric US data using the distribution of backscatter US data recovered from end-user displayed Bmode image available in clinical systems. To this end, we first propose the computation of a large set of features based on the homodyned-K distribution of the speckle as well as the correlation coefficients between small patches in 3D images. We then utilize the random forests framework to select the most important features for classification. Experiments on in-vivo 3D US data from nine pediatric patients with hydronephrosis showed an average accuracy of 94% for the classification of liver and kidney tissues showing a good potential of this work to assist in the classification and segmentation of abdominal soft tissue.

Citation Download Citation

Fereshteh Aalamifar, Hassan Rivaz, Juan J. Cerrolaza, James Jago, Nabile Safdar M.D., Emad M. Boctor, and Marius George Linguraru "Classification of kidney and liver tissue using ultrasound backscatter data", Proc. SPIE 9419, Medical Imaging 2015: Ultrasonic Imaging and Tomography, 94190X (17 March 2015); https://doi.org/10.1117/12.2082300

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