publication . Article . Other literature type . Conference object . Preprint . 2015

Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization

J. Alison Noble; Daniel Y. F. Chung; Omar S. Al-Kadi; Omar S. Al-Kadi; Robert Carlisle; Constantin C. Coussios;
Open Access English
  • Published: 01 Apr 2015 Journal: Medical Image Analysis, volume 21, issue 1, pages 59-71 (issn: 1361-8415, eissn: 1361-8423, Copyright policy)
  • Publisher: Elsevier
Graphical abstract
ACM Computing Classification System: ComputingMethodologies_COMPUTERGRAPHICS
free text keywords: Article, Texture analysis, Fractal dimension, Tumor characterization, Nakagami modeling, Ultrasound imaging, Radiological and Ultrasound Technology, Health Informatics, Radiology Nuclear Medicine and imaging, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computer Science - Computer Vision and Pattern Recognition, Ultrasonic sensor, Spatial frequency, Biological system, Computer vision, Fractal, Voxel, computer.software_genre, computer, Speckle pattern, Nakagami distribution, Image texture, Artificial intelligence, business.industry, business, Computer science
39 references, page 1 of 3

Al-Kadi, O., 2009. Tumour Grading and Discrimination Based on Class Assignment and Quantitative Texture Analysis Techniques, Thesis, Department of Informatics.

Al-Kadi, O., Watson, D.. Texture analysis of aggressive and non-aggressive lung tumor CE CT images. IEEE Trans. Biomed. Eng.. 2008; 55 (7): 1822-1830 [PubMed]

American Cancer Society, 2014. Cancer Facts and Statistics, Report, American Cancer Society. <> (accessed 25.06.14).

Anderson, M.E., Trahey, G.E., 2006. A Seminar on k-Space Applied to Medical Ultrasound, Department of Biomedical Engineering, Duke University.

Bae, Y.H., Mrsny, R.J., Park, K.. 2013

Bamber, J.C., Dickinson, R.J.. Ultrasonic b-scanning – a computer-simulation. Phys. Med. Biol.. 1980; 25 (3): 463-479 [OpenAIRE] [PubMed]

Bouhlel, N., Sevestre-Ghalila, S.. Nakagami markov random field as texture model for ultrasound RF envelope image. Comput. Biol. Med.. 2009; 39 (6): 535-544 [OpenAIRE] [PubMed]

Cancer Research UK, 2014. Cancer Stats Report – Liver Cancer, Report, Cancer Research U K. <> (accessed 25.06.14).

Cheng, J.L., Beaulieu, N.C.. Maximum-likelihood based estimation of the Nakagami m parameter. IEEE Commun. Lett.. 2001; 5 (3): 101-103

Chicklore, S., Goh, V., Siddique, M., Roy, A., Marsden, P.K., Cook, G.J.R.. Quantifying tumour heterogeneity in f-18-fdg pet/ct imaging by texture analysis. Eur. J. Nucl. Med. Mol. Imag.. 2013; 40 (1): 133-140

Coifman, R.R., Wickerhauser, M.V.. Entropy-based algorithms for best basis selection. IEEE Trans. Inform. Theory. 1992; 38 (2): 713-718 [OpenAIRE]

Czarnota, G., Sadeghi-Naini, A., Papanicolau, N., Falou, O., Dent, R., Verma, S., Trudeau, M., Boileau, J.-F., Spayne, J., Iradji, S., Sofroni, E., Lee, J., Lemon-Wong, S., Yaffe, M., Kolios, M.. Quantitative ultrasound evaluation of tumor cell death response in locally advanced breast cancer patients to chemotherapy treatment administration. J. Acoust. Soc. Am.. 2013; 133 (5): 3539

Daubechies, I.. The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inform. Theory. 1990; 36 (5): 961-1005

Daubechies, I.. 1992

Davnall, F., Yip, C.S.P., Ljungqvist, G., Selmi, M., Ng, F., Sanghera, B., Ganeshan, B., Miles, K.A., Cook, G.J., Goh, V.. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?. Insights Imag.. 2012; 3 (6): 573-589 [OpenAIRE]

39 references, page 1 of 3
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