Statistics of Boundaries in Ultrasonic B-Scan Images |
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| Institution: | 1. Institut Mines-Telecom, Telecom ParisTech, CNRS LTCI, 46 rue Barrault, 75013 Paris, France;2. Maternité Port Royal AP-HP, Groupe Hospitalier Cochin Saint Vincent de Paul, 53 Avenue de l’Observatoire, 75014 Paris, France;1. Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan;2. Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan, Taiwan;3. Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan;4. Biomedical Engineering Center, College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China;5. Department of Surgery, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan;1. Department of Computer Science & Engineering, Chitkara University Institute of Engineering & Technology, Chitkara University, Baddi, Himachal Pradesh, India;2. Department of Computer Science & Engineering, University Institute of Engineering & Technology, Panjab University, Chandigarh, Punjab, India;1. Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia;2. Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California;1. Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan;2. Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan;3. Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan, Taiwan;4. Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan, Taiwan;5. Department of Mathematics, National Cheng Kung University, Tainan, Taiwan |
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| Abstract: | The existence of edges and boundaries in regions of interest (ROIs) in B-scan images alters the statistics of the backscattered echo from the ROI. Boundaries are the result of at least two different types of scattering scenarios in tissue, and the Nakagami model, which is being used extensively in ultrasound, is unlikely to fit the statistics of the backscattered echo under these conditions. Furthermore, there are very few other statistical models exist that describe the statistics of the backscattered echo from regions containing boundaries. In this work, the gamma mixture density and the recently proposed McKay density are explored as two viable models to fill this void. Justifications of these models are presented along with methods for estimating their parameters. Random number simulations and studies on tissue-mimicking phantoms indicate that the McKay and gamma mixture densities are the best for the modeling of the backscattered echo intensity when boundaries are present in the regions of interest. |
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| Keywords: | Ultrasonic tissue characterization Microcalcifications Nakagami density Gamma density Gamma mixture Gamma sum McKay density Speckle factor Phantoms Edges and boundaries |
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