The Effect of Breast Composition on a No-reference Anisotropic Quality Index for Digital Mammography

详细信息    查看全文

• 关键词：Breast anatomy ; Image quality index ; Anisotropy ; Digital mammography
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9699
• 期：1
• 页码：226-233
• 全文大小：814 KB
• 参考文献：1.Li, Y., Poulos, A., Mclean, D., Rickard, M.: A review of methods of clinical image quality evaluation in mammography. Eur. J. Radiol. 74, e122–e131 (2010). doi:10.​1016/​j.​ejrad.​2009.​04.​069 CrossRef
  2.Wang, Z., Bovik, A.C.: Modern image quality assessment. Synth. Lect. Image Video Multimed. Process. (2006). doi:10.​2200/​S00010ED1V01Y200​508IVM003
  3.Oliveira, H.C.R., Barufaldi, B., Borges, L.R., Gabarda, S., Bakic, P.R., Maidment, A.D.A., Schiabel, H., Vieira, M.A.C.: Validation of no-reference image quality index for the assessment of digital mammographic images. In: SPIE Med Imaging, San Diego, CA, p. 978713-2 (2016). doi:10.​1117/​12.​2217229
  4.Bakic, P.R., Pokrajac, D.D., De Caro, R., Maidment, A.D.: Realistic simulation of breast tissue microstructure in software anthropomorphic phantoms. In: Fujita, H., Hara, T., Muramatsu, C. (eds.) IWDM 2014. LNCS, vol. 8539, pp. 348–355. Springer, Heidelberg (2014). doi:10.​1007/​978-3-319-07887-8_​49
  5.Bakic, P.R., Zhang, C., Maidment, A.D.A.: Development and characterization of an anthropomorphic breast software phantom based upon region-growing algorithm. Med. Phys. 38, 3165–3176 (2011). doi:10.​1118/​1.​3590357 CrossRef
  6.Gabarda, S., Cristóbal, G.: Blind image quality assessment through anisotropy. J. Opt. Soc. Am. Opt. Image Sci. Vis. 24, B42–B51 (2007). doi:10.​1364/​JOSAA.​24.​000B42 CrossRef
  
• 作者单位：Bruno Barufaldi (16) (17)
  Lucas R. Borges (16) (17)
  Marcelo A. C. Vieira (16)
  Salvador Gabarda (18)
  Andrew D. A. Maidment (17)
  Predrag R. Bakic (17)
  David D. Pokrajac (19)
  Homero Schiabel (16)
  
  16. Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, Brazil
  17. Department of Radiology, University of Pennsylvania, Philadelphia, USA
  18. Spanish Council for Scientific Research, Institute of Optics, Madrid, Spain
  19. Department of Information and Computer Sciences, Delaware State University, Dover, USA
  
• 丛书名：Breast Imaging
• ISBN：978-3-319-41546-8
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9699

文摘

There are several methods to evaluate objectively the quality of a digital image. For digital mammography, objective quality assessment must be performed without references. In a previous study, the authors investigated the use of a normalized anisotropic quality index (NAQI) to assess mammography images blindly in terms of noise and spatial resolution. Since the NAQI is used as a quality metric, it must not be highly dependent on the breast anatomy. Thus, in this work, we analyze the NAQI behavior with different breast anatomies. A computerized system was used to synthesize 2,880 anthropomorphic breast phantom images with a realistic range of anatomical variations. The results show that NAQI is only marginally dependent on breast anatomy when images are acquired without degradation (<12 %). However, for realizations that simulate the acquisition process in digital mammography, the NAQI is more sensitive (33 %) to variations arising from quantum noise. Thus, NAQI can be used in clinical practice to assess mammographic image quality.