Real-time spatial compound imaging in breast ultrasound

Huber, Sabine; Wagner, Monika; Medl, M.; Czembirek, H

doi:10.1016/s0301-5629(01)00490-2

Cited by 106 publications

(84 citation statements)

References 28 publications

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“…In the resulting images, the structural targets show consistently strong echoes while speckles show reduction in the brightness Consequently, the structural targets in spatially compounded images are enhanced and variations in the soft tissues due to speckle noise are averaged out [16]. This has been demonstrated both in vitro [14,17] and in vivo [11,[18][19][20][21][22]. These results indicate that spatial compounding can enhance the delineation of the boundaries and internal structure of lesions.…”

Section: Introductionsupporting

confidence: 48%

Spatial Compounding of Ultrasonic Diagnostic Images for Rotating Linear Probe with Geometric Parameter Error Compensation

Choi¹,

Bae²

2014

Journal of Electrical Engineering and Technology

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-In ultrasonic medical imaging, spatial compounding of images is a technique where ultrasonic beam is steered to examine patient tissues in multiple angles. In the conventional ultrasonic diagnostic imaging, the steering of the ultrasonic beam is achieved electronically using the phased array transducer elements. In this paper, a spatial compounding approach is presented where the ultrasonic probe element is rotated mechanically and the beam steering is achieved mechanically. In the spatial compounding, target position is computed using the value of the rotation axis and the transducer array angular position. However, in the process of the rotation mechanism construction and the control system there arises the inevitable uncertainties in these values. These geometric parameter errors result in the target position error, and the consequence is a blurry compounded image. In order to reduce these target position errors, we present a spatial compounding scheme where error correcting transformation matrices are computed and applied to the raw images before spatial compounding to reduce the blurriness in the compounded image. The proposed scheme is illustrated using phantom and live scan images of human knee, and it is shown that the blurriness is effectively reduced.

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Section: Introductionsupporting

confidence: 48%

Spatial Compounding of Ultrasonic Diagnostic Images for Rotating Linear Probe with Geometric Parameter Error Compensation

Choi¹,

Bae²

2014

Journal of Electrical Engineering and Technology

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“…Conclusions. Adaptive processing provided better image quality without loss of clinically useful information.Key Words: diagnostic imaging, medical electronics, image enhancement, ultrasonography (Invest Radiol 2003;38: 257-262) M any innovative technologies, such as harmonic imaging 1-4 and real-time compound imaging (SonoCT imaging), [5][6][7][8] have been introduced over the past several years to improve ultrasound (US) image quality. Real-time processing involving adaptive image analysis and enhancement (XRES imaging) is one of the latest commercially available US techniques.…”

mentioning

confidence: 99%

“…M any innovative technologies, such as harmonic imaging [1][2][3][4] and real-time compound imaging (SonoCT imaging), [5][6][7][8] have been introduced over the past several years to improve ultrasound (US) image quality. Real-time processing involving adaptive image analysis and enhancement (XRES imaging) is one of the latest commercially available US techniques.…”

mentioning

confidence: 99%

Application of Adaptive Image Processing Technique to Real-Time Spatial Compound Ultrasound Imaging Improves Image Quality

Meuwly¹,

Thiran²,

Gudinchet³

2003

Investigative Radiology

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Rationale and Objectives. To assess the impact of adaptive filter postprocessing on quality of ultrasound images. Methods. Ultrasound images acquired with real-time spatial compound imaging (SonoCT imaging) were subsequently processed with an adaptive real time algorithm (XRES imaging). Conventional and XRES-processed images from abdominal, pediatric or small parts ultrasound explorations were compared. The delineation of borders, tissue contrast, amount of noise, and overall image quality were evaluated. Results. Delineation of borders and tissue contrast were improved on all images (P Ͻ 0.05). The amount of noise was reduced (P Ͻ 0.05). The overall image quality was improved for abdominal, pediatric and small parts ultrasound explorations (P Ͻ 0.05). No image degradation was found. Conclusions. Adaptive processing provided better image quality without loss of clinically useful information.Key Words: diagnostic imaging, medical electronics, image enhancement, ultrasonography (Invest Radiol 2003;38: 257-262) M any innovative technologies, such as harmonic imaging 1-4 and real-time compound imaging (SonoCT imaging), [5][6][7][8] have been introduced over the past several years to improve ultrasound (US) image quality. Real-time processing involving adaptive image analysis and enhancement (XRES imaging) is one of the latest commercially available US techniques. It derives from processing of digital signals and is based on research originally performed for use in enhancing MRI images. With this technology, the US image, initially constructed by the scan converter of the device, is further refined in real time by an adaptive algorithm prior to display on the screen.XRES imaging is considered adaptive because it adapts its processing automatically to the nature of the target, both locally (ie, within an individual image) and temporally (over time from image to image). This adaptability is achieved in XRES by having both an analysis phase, in which both real tissue structures and ultrasound artifacts are identified, and an enhancement phase, in which structures identified in the analysis phase are enhanced and artifacts are suppressed. The analysis phase of XRES takes into account many characteristics of the image, such as textural and structural properties including gradients and local statistics. The results of this analysis directly control the enhancement phase; for example, smoothing is applied along an interface to improve continuity, whereas edge enhancement is applied in the perpendicular direction to improve spatial resolution. In regions identified by the analysis phase as being relatively homogeneous (containing minimal structure or texture), smoothing is applied equally in all directions to suppress speckle and noise. Thus XRES is designed both to suppress artifacts and to enhance interfaces and margins. In addition, XRES is a multiresolution algorithm. This means that all processinganalysis and enhancement-occurs at multiple scales within the image. Multiresolution processing improves robustness by all...

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“…Moreover, occlusion artifacts below structures with high acoustic impedance can be removed and the boundary continuity is enhanced. The positive effects of spatial compounding for diagnosis of atherosclerotic plaques [12,13] and breast cancer [2] have already been reported. It also helps for administering epidural anesthesia by especially improving the depiction of key structures such as ligamentum flavum and epidural space [19].…”

Section: Clinical Value Of Compoundingmentioning

confidence: 99%

Estimation of acoustic impedance from multiple ultrasound images with application to spatial compounding

Wachinger

Shams

Navab

2008

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

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Reflection of sound waves, due to acoustic impedance mismatch at the interface of two media, is the principal physical property which allows visualization with ultrasound. In this paper, we investigate reconstruction of the acoustic impedance from ultrasound images for the first time. Similar to spatial compounding, we combine multiple images to improve the estimation. We use phase information to determine regions of high reflection from an ultrasound image. We model the physical imaging process with an emphasis on the reflection of sound waves. The model is used in computing the acoustic impedance (up to a scale) from areas of high reflectivity. The acoustic impedance image can either be directly visualized or be used in simulation of ultrasound images from an arbitrary point of view. The experiments performed on in-vitro and in-vivo data show promising results.

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Real-time spatial compound imaging in breast ultrasound

Cited by 106 publications

References 28 publications

Spatial Compounding of Ultrasonic Diagnostic Images for Rotating Linear Probe with Geometric Parameter Error Compensation

Spatial Compounding of Ultrasonic Diagnostic Images for Rotating Linear Probe with Geometric Parameter Error Compensation

Application of Adaptive Image Processing Technique to Real-Time Spatial Compound Ultrasound Imaging Improves Image Quality

Estimation of acoustic impedance from multiple ultrasound images with application to spatial compounding

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