ACUSON Sequoia™ Ultrasound System UltraArt™ Universal Image Processing

This white paper contains information on how UltraArt universal image processing uses speckle reduction techniques to increase image quality when using the ACUSON Sequoia system.

White Paper UltraArt Universal Image Processing ACUSON Sequoia Ultrasound System Mikyoung Park, MSEE, Siemens Medical Solutions USA, Inc., Ultrasound HOOD05162003028886 · Effective Date: 2-Aug-2019 SIEMENS Healthineers UltraArt · White Paper Introduction Due to the nature of coherent image formation of UltraArt™ universal image processing is a state of-the-art ultrasound, speckle is an inherent property of ultrasound speckle reduction algorithm, developed by Siemens images. Speckle is seen as a random granular pattern Healthineers to reduce speckle, enhance ridges of caused by the constructive and destructive interference directional structures and sharpen edges prior to image of back scattered echoes from scatterers much smaller interpretation without losing important features (e.g., than the ultrasound imaging wavelength. The presence small, low-contrast structures and texture information), of speckle degrades the detail and contrast resolution of thus improving image detail and contrast resolution. ultrasound images and makes diagnosis more difficult. Speckle ReductionTechniques Various techniques have been developed and 2. Post-processing based techniques implemented to reduce speckle in research institutions and the ultrasound industry. These techniques can be Speckle reduction is achieved through single image categorized into two broad areas: (1) Compounding/ frame post-processing techniques include linear filtering Averaging-based techniques and (2) Post-processing [1–3], median filtering [4], Lee filtering [5], Wiener based techniques. filtering [6], anisotropic diffusion filtering [7–9], and wavelet denoising filtering [10–11]. Siemens Healthineers 1. Compounding/Averaging-based techniques DTCE [12], ContextVision [13], GE SRI [14] and Philips XRES [15] are commercially available proprietary post- Speckle reduction is achieved by combining uncorrelated processing techniques for this purpose. images. In spatial compounding, several overlapping uncorrelated component image frames are acquired from Current speckle reduction techniques reduce speckle to different view angles, and then combined into a single various extents, however, it is common to see excessive compounded image. In frequency compounding, blurring and an artificial image appearance. As a result, uncorrelated sub-images are obtained by either varying important features may be lost or obscured after the center frequency on transmission or by dividing the performing speckle reduction. spectrum of RF signals on reception, and recombining to form a frequency averaged image. In temporal averaging (known as persistence), successive image frames that are uncorrelated through tissue or probe motion are combined into a single image. 2 HOOD05162003028886 · Effective Date: 2-Aug-2019 White Paper · UltraArt UltraArt universal image processing UltraArt universal image processing is a state-of-the- In terms of clinical workflow, UltraArt universal image art post-processing algorithm developed by Siemens processing is designed to improve: Healthineers utilizing our in-depth understanding • of ultrasound image characteristics and clinical Plunkability: reduces speckle and increases continuity applications / anatomies to improve diagnostic of specular reflectors, and thus improves contrast confidence. It is implemented not only for B-mode resolution but also for M-mode, Doppler and contrast modes • Usability: reduces complexity, redundancy and on the new ACUSON Sequoia™ ultrasound system. interplay of image processing features, and unifies them under a simple and intuitive user interface • Enables robust image presentation and aesthetics User Interface (UI) Traditional post-processing user controls are often non- intuitive, complex and redundant which can prevent users from choosing an ideal combination. UltraArt universal image processing introduces a simple and intuitive image-based graphical user interface. Traditional user controls are replaced by a set of images, each corresponding to a different set of image processing parameters applied to a common input image. The user picks one of the images from the set, based on the desired outcome on the touch screen interface, which determines the UltraArt universal image processing parameters for the exam until a different selection is made. Figure 1 illustrates the UltraArt universal image processing UI. Figure 1: The all new ACUSON Sequoia ultrasound system 3 HOOD05162003028886 · Effective Date: 2-Aug-2019 UltraArt · White Paper 2 Patient Imaging Review Report End Exam Off + 00:00:59 Panoramic Figure 2: Simple and intuitive image-based UI Left Margin showing different levels of image enhancement. Algorithm Description There are three major components of image enhancement Two edges can be detected at either side of a ridge. for UtraArt universal image processing: speckle reduction, Figure 2 illustrates the major image components. ridge enhancement and edge sharpening. Speckle is a UltraArt universal image processing is designed to control granular pattern most noticeable within echogenic area the enhancement of these three major components (e.g., tissue). Ridges are formed where the gray value independently so that ultrasound images can be reaches local maxima in a given direction (e.g., bright customized to meet clinical needs. The philosophy structures). Edges are borders between areas of high and of UltraArt universal image processing optimization low gray values. is preserving information and maintaining natural tissue texture, rather than drastic filtering. Figure 3 illustrates the UltraArt universal image processing 3 universal image processing signal path. Speckle is reduced by utilizing speckle statistics and echogenicity similarity information while preserving edges of structures and, most importantly, preserving authentic tissue texture (e.g., liver tissue). Anisotropic filters are used to detect and enhance ridges of directional structures. Image analysis identifies the location, strength and direction of edges in the images at multiple spatial scales. Edges are enhanced and/or smoothed via adaptive sharpening/smoothing filters. Finally, local contrast is enhanced by amplifying the difference between the luminance values of each pixel and its local region. Figure 3: Example areas of speckle (yellow circle), ridges (red solid line) and edges (green dash line) are highlighted in the thyroid image above. 4 HOOD05162003028886 · Effective Date: 2-Aug-2019 White Paper · UltraArt Touch Screen Interface T n (m, n) m Input Speckle Ridge Edge Local Output Image Reduction Enhance Enhance Adaptive DR Image Figure 4: Block diagram describing independent processing components and intermittent results using UltraArt universal image processing. UltraArt universal image processing Clinical Applications Abdomen Figure 5 shows a transverse cross section of (a) a liver with and improving contrast resolution in liver structures and hepatic vein and (c) a liver with longitudinal section of the the kidney (e.g., the echo differentiation between the kidney. Original images show a granular pattern in tissue continuity of cortex, medulla, and columns). Noise in the with noise observed inside the vein and kidney pyramid. vein and kidney pyramid is also suppressed, and structure In UltraArt universal image processing applied images, definition (vessel wall, diaphragm, interface between speckle is reduced while maintaining natural tissue texture kidney and liver, etc.) is improved. Figure 5: (a) & (c) Original images 5a 5b from curved transducer, (b) & (d) UltraArt universal image processing applied images. 5c 5d 5 HOOD05162003028886 · Effective Date: 2-Aug-2019 UltraArt · White Paper Thyroid Figure 6 shows thyroid images. In UltraArt universal while enhancing contrast resolution, details and edge image processing applied images, speckle in the sterno- structures. Structure boundaries (e.g., thyroid lobes, cleidomastoid muscle and thyroid gland is suppressed trachea, intima media) are better defined. 6a 6b Thyroid TIB:0.35 TIC:0.04 TIS:0.35 MI:1.01 42fpc 85 6c 6d 421po Figure 6: (a) & (c) Original images from linear transducer, whereas (b) & (d) UltraArt universal image 3.50% processing applied images. 6 HOOD05162003028886 · Effective Date: 2-Aug-2019 White Paper · UltraArt Figure 7 shows (a) parasternal long-axis and (c) apical Contrast resolution in the differentiation of the three-chamber echocardiography images. In UltraArt myocardium, endocardium, and pericardium is improved, universal image processing applied images (b, d), clutter and the continuity of the aortic and mitral valve is noise in the chamber is well suppressed as compared better defined. to the original image (a, c). 7a 7b 0da/DR59 MapC/T 7c 7d H Md JE/DROO LD 2 UA Oft MapOITS Figure 7: (a) & (c) Original images from vector transducer, whereas (b) & (d) UltraArt universal image processing applied ... images. Conclusion UltraArt universal image processing is an excellent diagnostic confidence and consistency across different ultrasound image processing algorithm that improves users by producing images of higher quality and by image quality across clinical applications. Clinical avoiding improper combinations of individual post- evaluations suggest that it reduces speckle while processing parameters. By allowing real time modification maintaining natural tissue texture, improves the of the level of speckle in the image, UltraArt universal continuity of structures, and creates better defined image processing empowers the user to customize the borders. All these enhancements improve image detail image to their unique preferences. In this way, UltraArt and contrast resolution. universal image processing on the ACUSON Sequoia system helps to expand precision medicine. Plunkability and usability improvements by UltraArt universal image processing can help in improving 7 HOOD05162003028886 · Effective Date: 2-Aug-2019 References 1. Dave Hale, “Recursive gaussian filters”, CWP-546, 2006. 8. K. Abd-Elmoniem, A.-B. Youssef, Y. Kadah, ‘‘Real-time speckle 2. L. Chen, G. Lu and D. Zhang, ‘’Effects of different gabor filter reduction and coherence enhancement in ultrasound imaging parameters on image retrieval by texture’’, In Proc. of IEEE via nonlinear anisotropic diffusion,’’ IEEE Trans. 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Imag., vol. 20, no. 8, pp. 772–783, 1981 2001. 6. Robert S. Caprari, Alvin S. Goh, and Emily K. Moffatt, “Noise and speckle reduction in synthetic aperture radar imagery by 12 nonparametric Wiener filtering,” Applied Optics. Vol.39, Issue 13. 35, pp.6633-6640, 2000. 14. 7. S. Jin, Y. Wang, J. Hiller, ‘‘An adaptive non-linear diffusion algorithm for filtering medical images,’’ IEEE Trans. Inform. 15. Technol. Biomed., vol. 4, no. 4, pp. 298–305, 2000. Standalone clinical images may have been cropped to better visualize pathology. The products/features mentioned in this document may not be commercially available in all countries. Due to regulatory reasons, their future availability cannot be guaranteed. Please contact your local Siemens Healthineers organization for further details. ACUSON Sequoia and UltraArt universal image processing are trademarks of Siemens Medical Solutions USA, Inc. Siemens Healthineers Headquarters Legal Manufacturer Siemens Healthcare GmbH Siemens Medical Solutions USA, Inc. Henkestr. 127 Ultrasound 91052 Erlangen, Germany 22010 S.E. 51st Street Issaquah, WA 98029 USA Phone: +49 9131 84-0 Phone: 1-888-826-9702 Published by Siemens Medical Solutions USA, Inc. · Order No. A91US-555-1C-4A00 · Printed in Germany · 7869 0819 © Siemens Medical Solutions USA, Inc., 2019 HOOD05162003028886 · Effective Date: 2-Aug-2019