Signal attenuation maps for needle enhancement and localization in 2D ultrasound

Mwikirize, Cosmas; Nosher, John L.; Hacihaliloglu, Ilker

doi:10.1007/s11548-017-1698-y

Cited by 16 publications

(32 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the amplitude of the Doppler responses generated by the excited needle might be reduced when the needle is inserted at high depths due to the damping of the needle vibrations by the surrounding tissue. Despite the depth-dependent degradation in the lateral resolution, many previous studies, such as [ 12 , 14 ], that proposed needle detection methods based on B-mode ultrasound image analysis showed that the needle can be localized in curvilinear ultrasound images with submillimeter accuracies. In fact, the method presented in the current study was also able to obtain accurate needle localization with submillimeter accuracy by combining power Doppler and B-mode ultrasound image analyses.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, the position of the needle tip along the estimated needle axis is determined using image statistical analysis. Mwikirize et al [ 14 ] introduced a method for enhancing the needle visibility and localizing the needle in curvilinear B-mode images. In this method, the visibility of the needle is enhanced by computing signal attenuation maps that model ultrasound attenuation and scattering.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the needle tip is estimated using statistical analysis that is similar to the analysis employed in [ 12 ]. In fact, the assumptions employed by the needle localization methods in [ 12 , 14 ], which include the assumptions about the a priori known insertion location of the needle and the assumption about the location of the visible part of the needle, might limit their application in real-life clinical procedures. In general, the performance of the needle localization methods that are based on B-mode image analysis is affected by the visibility of the needle in the B-mode ultrasound image.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Accurate Needle Localization Using Two-Dimensional Power Doppler and B-Mode Ultrasound Image Analyses: A Feasibility Study

Daoud

Shtaiyat

Zayadeen

et al. 2018

Sensors

View full text Add to dashboard Cite

Curvilinear ultrasound transducers are commonly used in various needle insertion interventions, but localizing the needle in curvilinear ultrasound images is usually challenging. In this paper, a new method is proposed to localize the needle in curvilinear ultrasound images by exciting the needle using a piezoelectric buzzer and imaging the excited needle using a curvilinear ultrasound transducer to acquire a power Doppler image and a B-mode image. The needle-induced Doppler responses that appear in the power Doppler image are analyzed to estimate the needle axis initially and identify the candidate regions that are expected to include the needle. The candidate needle regions in the B-mode image are analyzed to improve the localization of the needle axis. The needle tip is determined by analyzing the intensity variations of the power Doppler and B-mode images around the needle axis. The proposed method is employed to localize different needles that are inserted in three ex vivo animal tissue types at various insertion angles, and the results demonstrate the capability of the method to achieve automatic, reliable and accurate needle localization. Furthermore, the proposed method outperformed two existing needle localization methods.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Accurate Needle Localization Using Two-Dimensional Power Doppler and B-Mode Ultrasound Image Analyses: A Feasibility Study

Daoud

Shtaiyat

Zayadeen

et al. 2018

Sensors

View full text Add to dashboard Cite

show abstract

“…Recently, a template-based tracking method with the efficient second-order minimization optimization method has been used to track the needle [16]. In recent studies, more and more novel ideas have been used to locate the needle and evaluate its tip to sagittal US images, such as the use of signal attenuation maps [17], convolution neural networks (CNN) [18], and maximum likelihood estimation sample consensus (MLESAC) method [19]. However, a demerit of using sagittal US images is that out-of-plane bending of the needle cannot be detected.…”

Section: Introductionmentioning

confidence: 99%

Tip Estimation Method in Phantoms for Curved Needle Using 2D Transverse Ultrasound Images

Song

Liu

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

Flexible needles have been widely used in minimally invasive surgeries, especially in percutaneous interventions. Among the interventions, tip position of the curved needle is very important, since it directly affects the success of the surgeries. In this paper, we present a method to estimate the tip position of a long-curved needle by using 2D transverse ultrasound images from a robotic ultrasound system. Ultrasound is first used to detect the cross section of long-flexible needle. A new imaging approach is proposed based on the selection of numbers of pixels with a higher gray level, which can directly remove the lower gray level to highlight the needle. After that, the needle shape tracking method is proposed by combining the image processing with the Kalman filter by using 3D needle positions, which develop a robust needle tracking procedure from 1 mm to 8 mm scan intervals. Shape reconstruction is then achieved using the curve fitting method. Finally, the needle tip position is estimated based on the curve fitting result. Experimental results showed that the estimation error of tip position is less than 1 mm within 4 mm scan intervals. The advantage of the proposed method is that the shape and tip position can be estimated through scanning the needle’s cross sections at intervals along the direction of needle insertion without detecting the tip.

show abstract

“…More recently, attenuation of the US signal due to energy loss beyond the US beam incident with the needle, is used to detect the position of the needle [ 8 , 11 ]. However, signal loss due to the presence of other attenuating structures may degrade the accuracy of estimation and must be explicitly handled.…”

Section: Introductionmentioning

confidence: 99%

Robust and semantic needle detection in 3D ultrasound using orthogonal-plane convolutional neural networks

et al. 2018

View full text Add to dashboard Cite

PurposeDuring needle interventions, successful automated detection of the needle immediately after insertion is necessary to allow the physician identify and correct any misalignment of the needle and the target at early stages, which reduces needle passes and improves health outcomes.MethodsWe present a novel approach to localize partially inserted needles in 3D ultrasound volume with high precision using convolutional neural networks. We propose two methods based on patch classification and semantic segmentation of the needle from orthogonal 2D cross-sections extracted from the volume. For patch classification, each voxel is classified from locally extracted raw data of three orthogonal planes centered on it. We propose a bootstrap resampling approach to enhance the training in our highly imbalanced data. For semantic segmentation, parts of a needle are detected in cross-sections perpendicular to the lateral and elevational axes. We propose to exploit the structural information in the data with a novel thick-slice processing approach for efficient modeling of the context.ResultsOur introduced methods successfully detect 17 and 22 G needles with a single trained network, showing a robust generalized approach. Extensive ex-vivo evaluations on datasets of chicken breast and porcine leg show 80 and 84% F1-scores, respectively. Furthermore, very short needles are detected with tip localization errors of less than 0.7 mm for lengths of only 5 and 10 mm at 0.2 and 0.36 mm voxel sizes, respectively.ConclusionOur method is able to accurately detect even very short needles, ensuring that the needle and its tip are maximally visible in the visualized plane during the entire intervention, thereby eliminating the need for advanced bi-manual coordination of the needle and transducer.

show abstract

Signal attenuation maps for needle enhancement and localization in 2D ultrasound

Abstract: The proposed method could be useful in challenging procedures where needle shaft and tip are inconspicuous. Improved needle localization results compared to previously proposed methods suggest that the proposed method is promising for further clinical evaluation.

Cited by 16 publications

References 17 publications

Accurate Needle Localization Using Two-Dimensional Power Doppler and B-Mode Ultrasound Image Analyses: A Feasibility Study

Accurate Needle Localization Using Two-Dimensional Power Doppler and B-Mode Ultrasound Image Analyses: A Feasibility Study

Tip Estimation Method in Phantoms for Curved Needle Using 2D Transverse Ultrasound Images

Robust and semantic needle detection in 3D ultrasound using orthogonal-plane convolutional neural networks

Contact Info

Product

Resources

About