3D ultrasound in cardiology

Antonio J Bravo, Miguel Vera, Delia Madriz, Julio Contreras-Velásquez, José Chacón, Sandra Wilches-Durán, Modesto Graterol-Rivas, Daniela Riaño-Wilches, Joselyn Rojas, Valmore Bermúdez

Article ID: 1748
Vol 5, Issue 1, 2022

VIEWS - 528 (Abstract) 298 (PDF)

Abstract


Cardiovascular imaging analysis is a useful tool for the diagnosis, treatment and monitoring of cardiovascular diseases. Imaging techniques allow non-invasive quantitative assessment of cardiac function, providing morphological, functional and dynamic information. Recent technological advances in ultrasound have made it possible to improve the quality of patient treatment, thanks to the use of modern image processing and analysis techniques. However, the acquisition of these dynamic three-dimensional (3D) images leads to the production of large volumes of data to process, from which cardiac structures must be extracted and analyzed during the cardiac cycle. Extraction, three-dimensional visualization, and qualification tools are currently used within the clinical routine, but unfortunately require significant interaction with the physician. These elements justify the development of new efficient and robust algorithms for structure extraction and cardiac motion estimation from three-dimensional images. As a result, making available to clinicians new means to accurately assess cardiac anatomy and function from three-dimensional images represents a definite advance in the investigation of a complete description of the heart from a single examination. The aim of this article is to show what advances have been made in 3D cardiac imaging by ultrasound and additionally to observe which areas have been studied under this imaging modality.


Keywords


Ultrasound; Acquisition; Visualization; Processing; Reconstruction; Cardiology

Full Text:

PDF


References


1. Nelson TR, Downey DB, Pretorius DH, et al. Three-dimensional ultrasound. Philadelphia: Lippincott Williams & Wilkins; 1999.

2. Kremkau FW. Diagnostic ultrasound: Principles and instruments. Philadelphia: W.B. Saunders Company; 1993.

3. Geiser EA, Oliver LH. Echocardiography physics and intrumentation. In: Collins S, Skorton D (editors). Cardiac imaging and image processing. New York: McGraw Hill; 1980. p. 24–38.

4. Crawford D, Bell D, Bamber J. Compensation for the signal processing characteristic of ultra- sound b-mode scanners in adaptive speckle reduction. Ultrasound in Medicine & Biology 1993; 19(6): 469–485.

5. Nelson T, Pretorius D. 3D ultrasound image quality improvement using spatial compounding and 3D filtering. Medical Physics 1994; 21(6): 998–999.

6. Kotropoulos C, Magnisalis X, Pitas I, et al. Nonlinear ultrasonic image processing based on signal-adaptive filters and self-organizing neural networks. IEEE Transactionson Image Processing 1994; 3(1): 65–77.

7. Gronningsaeter A, Angelsen BAJ, Gresli A, et al. Blood noise reduction in intravascular ultrasound imaging. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 1995; 42(2): 200–209.

8. Fortes JMP. A closed loop ML algorithm for phase aberration correction in phased array imaging systems. I: Algorithm synthesis and experimental results [Ultrasound medical imaging]. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 1997; 44(2): 259–270.

9. Achim A, Bezerianos A, Tsakalides P. Novel bayesian multiscale method for speckle removal in medical ultrasound images. IEEE Transaction on Medical Imaging 2001; 20(8): 772–783.

10. Hajnal JV, Hill DLG, Hawkes DJ. Medical image registration. New York: CRC Press LLC; 2001.

11. Zhang X, McKay CR, Sonka M. Tissue characterization in intravascular ultrasound imaging. IEEE Transaction on Medical Imaging 1998; 17(6): 889–899.

12. Canals R, Lamarque G, Chatain P. Volumetric ultrasound system for left ventricle motion imaging. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 1999; 46(6): 1527–1538.

13. Light ED, Idriss SF, Wolf PD, et al. Real-time three-dimensional intracardiac echocardiography. Ultrasound in Medicine & Biology 2002; 27(9): 1177–1183.

14. Xiao G, Brady JM, Noble JA, et al. Nonrigid registration of 3D free-hand ultrasound images of the breast. IEEE Transaction on Medical Imaging 2002; 21(4): 405–412.

15. Deng J, Sullivan ID, Yates R, et al. Real-time three-dimensional fetal echocardiography—Optimal imaging windows. Ultrasound in Medicine & Biology 2002; 28(9): 1099–1105.

16. Volkmer BG, Nesslauer T, Kuefer R, et al. Visualization of urinary stones by 3D ultrasound with surface rendering. Ultrasound in Medicine & Biology 2002; 28(2): 143–147.

17. Pretorius DH, Nelson TR. Three-dimensional ultrasound. Ultrasound in Obstetrics and Gynecology 1995; 5: 219–221.

18. Fenster A, Downey DB. 3D ultrasound imaging: A review. IEEE Engineering in Medicine and Biology 1996; 15(6): 41–51.

19. Raab FH, Blood EB, Steiner TO, et al. Magnetic position and orientation tracking system. IEEE Transaction on Aerospace and Electronic Systems 1979; 15(15): 709–717.

20. Birkfellner W, Watzinger F, Wanschitz F, et al. Systematic distortions in magnetic position digitizers. Medical Physics 1998; 25(11): 2242–2248.

21. Moritz WE, Pearlman AS, McCabe DH, et al. An ultrasonic technique for imaging the ventricle in three dimensions and calculating its volume. IEEE Transaction on Biomedical Engineering 1983; 30(8): 482–492.

22. Sato Y, Nakamoto M, Tamaki Y, et al. Image guidance of breast cancer surgery using 3D ultra-sound images and augmented reality visualization. IEEE Transaction on Medical Imaging 1998; 17(5): 681–693.

23. Martin RW, Bashein G, Detmer PR, et al. Ventricular volume measurement from a multiplanar transplanar transesophageal ultrasonic imaging systems: An in vitro study. IEEE Transaction on Biomedical Engineering 1990; 37(5): 442–449.

24. Smith SW, Pavy HE, von Ramm OT. High speed ultrasound volumetric imaging system part I: Transducer design and beam steering. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control 1991; 38(2): 100–108.

25. Light ED, Davidsen RE, Fiering JO, et al. Progress in two dimensional arrays for real time volumetric imaging. Ultrasonic Imaging 1998; 20(1): 1–18.

26. Klingensmith JD, Shekhar R, Vince DG. Evaluation of three-dimensional segmentation algorithms for the identification of luminal and medial-adventiti- al borders in intravascular ultrasound images. IEEE Transactions on Medical Imaging 2000; 19(10): 996–1011.

27. Woods R. Handbook of medical image processing and analysis. San Diego: Academic Press; 2000.

28. Prager RW, Rohling RN, Gee AH, et al. Rapid calibration for 3-D freehand ultrasound. Ultrasound in Medicine & Biology 1998; 24(6): 855–869.

29. Rohling R, Gee A, Berman L. A comparison of freehand three-dimensional ultrasound reconstruction techniques. Medical Image Analysis 1999; 3(4): 339–359.

30. Aiger D, Cohen-Or D. Mosaicing ultrasonic volumes for visual simulation. IEEE Computer Graphics and Applications 2000; 20(2): 53–61.

31. Krücker JF, Meyer CR, LeCarpentier GL, et al. 3D spatial compounding of ultrasound images using image-based nonrigid registration. Ultrasound in Medicine & Biology 2000; 26(9): 1475–1488.

32. Tong S, Cardinal HN, McLoughlin RF, et al. Intra- and inter-observer variability and reliability of prostate volume measurement via two-dimensional and three-dimensional ultrasound imaging. Ultrasound in Medicine & Biology 1998; 24(5): 673–681.

33. Cardinal HN, Gill JD, Fenster A. Analysis of geometrical distortion and statistical variance in length, area, and volume in a linearly scanned 3-D ultrasound image. IEEE Transactions on Medical Imaging 2000; 19(6): 632–651.

34. Dias JMB, Leitao JMN. Wall position and thickness estimation from sequences of echocardiographic images. IEEE Transactions on Medical Imaging 1996; 15(1): 25–38.

35. Xiao G, Brady M, Noble JA, et al. Segmentation of ultrasound b-mode images with intensity inhomogeneity correction. IEEE Transactions on Medical Imaging 2002; 21(1): 48–57.

36. Setarehdan GK, Soraghan JJ. Automatic cardiac LV boundary detection and tracking using hybrid fuzzy temporal and fuzzy multiscale edge detection. IEEE Transactions on Biomedical Engineering 1999; 46(11): 1364–1378.

37. Coppini G, Poli R, Valli G. Recovery of the 3D shape of the left ventricle from echocardiographic images. IEEE Transactions on Biomedical Engineering 1996; 14(2): 301–317.

38. Detmer PR, Bashein G, Martin RW. Matched filter identification of left-ventricular endocardial borders in transesophageal echocardiograms. IEEE Transactions on Medical Imaging 1990; 9(4): 396–404.

39. Chalana V, Linker DT, Haynor DR, et al. A multiple active contour model for cardiac boundary detection on echocardiographic sequence. IEEE Transactions on Medical Imaging 1996; 15(6): 290–298.

40. Mikic I, Krucinski S, Thomas JD. Segmentation and tracking in echocardiographic sequences: Active contours guided by optical flow estimates. IEEE Transactions on Medical Imaging 1998; 17(2): 274–284.

41. Malassiotis S, Strintzis MG. Tracking the left ventricle in echocardio-graphic images by learning heart dynamics. IEEE Transactions on Medical Imaging 1999; 18(3): 282–290.

42. Jacob G, Noble JA, Behrenbruch C, et al. A shape- space-based approach to tracking myocardial borders and quantifying regional left-ventricular function applied in echocardiography. IEEE Transactions on Medical Imaging 2000; 21(3): 226–238.

43. Goldstein A. Errors in ultrasound digital image distance measurements. Ultrasound in Medicine & Biology 2000; 26(7): 1125–1132.

44. Stytz MR, Frieder G, Frieder O. Three-dimensional medical imaging: Algorithms and computer systems. ACM Computing Surveys 1991; 23(4): 421–499.

45. Nelson TR, Elvins TT. Visualization of 3D ultrasound data. IEEE Computer Graphics and Applications 1993; 13(6): 50–57.

46. Hauser H, Mroz L, Bischi GI, et al. Two-level volume rendering. IEEE Transactions on Visualization and Computer Graphics 2001; 7(3): 242–252.

47. Gill JD, Ladak HM, Steinman DA, et al. Accuracy and variability assessment of a semiautomatic technique for segmentation of the carotid arteries from three-dimensional ultrasound images. Medical Physics 2000; 27(6): 1333–1342.

48. Bardinet E, Cohen L, Ayache N. Tracking and motion analysis of the left ventricle with deformable superquadrics. Medical Image Analysis 1996; 1(2): 129–149.

49. Angelini ED, Laine AF, Takuma S, et al. LV volume quantification via spatiotemporal analysis of real- time 3D echocardiography. IEEE Transactions on Medical Imaging 2001; 20(2): 457–469.

50. Tang H, Zhuang T, Wu E. Realizations of fast 2D/3D image filtering and enhancement. IEEE Transactions on Medical Imaging 2001; 20(2): 132–140.

51. Wahle A, Prause GPM, DeJong SC, et al. Geometrically correct 3D reconstruction of intravascular ultrasound images by fusion with biplane angiography: Methods and validation. IEEE Transactions on Medical Imaging 1999; 18(8): 686–699.

52. Hossack JA, Sumanaweera TS, Napel S, et al. Quantitative 3D diagnostic ultrasound imaging using a modified transducer array and an automated image tracking technique. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control 2002; 38(2): 1029–1038.

53. Abolmaesumi P, Salcudean SE, Zhu W, et al. Image-guided control of a robot for medical ultrasound. IEEE Transaction on Robotics and Automation 2002; 18(1): 11–23.

54. Gérard O, Billon AC, Rouet JM, et al. Efficient model-based quantification of left ventricular function in 3D echocardiography. IEEE Transactions on Medical Imaging 2002; 21(7): 1059–1068.




DOI: https://doi.org/10.24294/irr.v5i1.1748

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License

This site is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.