Ideal observer model for detection of blood perfusion and flow using ultrasound

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2732, Issue , 2003, Pages 318-329

  Zemp, Roger J ^a   Abbey, Craig K ^a   Insana, Michael F ^a  

^a University of California Davis   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BLOOD; MEDICAL IMAGING; RANDOM PROCESSES; TISSUE;

BLOOD PERFUSION; IDEAL OBSERVER MODELS; IDEAL OBSERVERS; NOISE EQUIVALENT QUANTA; OBJECT FUNCTIONS; OBJECT PARAMETERS; POWER DOPPLER; TASK PERFORMANCE;

ULTRASONIC APPLICATIONS;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BLOOD FLOW; BLOOD FLOW VELOCITY; BLOOD VESSEL; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; DOPPLER FLOWMETRY; ECHOGRAPHY; EVALUATION; FUNCTIONS OF THE HEMIC, LYMPHATIC AND RETICULOENDOTHELIAL SYSTEMS; IMAGE ENHANCEMENT; METHODOLOGY; PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; VALIDATION STUDY;

ALGORITHMS; BLOOD FLOW VELOCITY; BLOOD PHYSIOLOGY; BLOOD VESSELS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; LINEAR MODELS; MODELS, CARDIOVASCULAR; MODELS, STATISTICAL; REGIONAL BLOOD FLOW; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; ULTRASONOGRAPHY, DOPPLER;

EID: 35248894423     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-45087-0_27     Document Type: Article

References (10)

1. J. A. Jensen, Estimation of Blood Velocities Using Ultrasound: A Signal Processing Approach. New York: Cambridge Univ. Press, 1996.
2. K. W. Ferrara, C. W. Merritt, P. N. Burns, F. S. Foster, R. F. Mattrey, S. A. Wickline, "Evaluation of Tumor Angiogenesis with US: Imaging, Doppler, and Contrast Agents," Acad. Radiol. Vol. 7, pp. 824-839, 2000.
3. C. Kasai, K. Namekawa, A. Koyano, R. Omoto, "Real-time two-dimensional blood flow imaging using an autocorrelation technique. IEEE Trans. Sonics Ultrason. SU-32, pp. 458-464.
4. G. E. Trahey, J. W. Allison, and O. T. von Ramm, "Angle independent ultrasonic detection of blood flow," IEEE Trans. Biomed. Eng. Vol. 34, pp. 965-967, 1987.
5. J. M. Rubin, R. O. Bude, P. L. Carson, R. L. Bree, R. S. Alder, "Power Doppler US: A Potentially Useful Alternative to Mean-Frequency-based Color Doppler US," Radiology, Vol. 190, pp. 853-856, 1994.
6. R. J. Zemp, C. K. Abbey, M. F. Insana, "Linear system models of ultrasound imaging: Application to signal statistics," IEEE Trans. Ultrason., Ferroelect., Freq. Contr., To be published.
7. R. J. Zemp, C. K. Abbey, M. F. Insana, "Generalized NEQ for assessment of ultrasound image quality," Proc. SPIE Medical Imaging, San Diego, CA, 2003.
8. R. F. Wagner, M. F. Insana, and D. G. Brown, "Statistical properties of radio-frequency and envelope-detected signals with applications to medical ultrasound," J. Opt. Soc. Am. A, Vol. 4, pp. 910-922, 1987.
9. H. H. Barrett, "Objective assessment of image quality: effects of quantum noise and object variability," J. Opt. Soc. Am. A, Vol. 7, pp. 1266-1278, 1990.
10. R. F. Wagner and D. G. Brown, "Unified SNR analysis of medical imaging systems," Phys. Med. Biol. Vol. 30, pp. 489-518, 1985.