Displacement Field Estimation for Echocardiography Strain Imaging Using B-Spline Based Elastic Image Registration—Synthetic Data Study

Wilczewska, Aleksandra; Cygan, Szymon; Żmigrodzki, Jakub

doi:10.1007/978-3-319-46490-9_42

Cited by 3 publications

(4 citation statements)

References 11 publications

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“…In this work, the regularization of the original optical flow implementation of Horn & Schunck, also included a term enforcing incompressibility of the matter under observation. The idea to use incompressibility as a sensible constraint has also been subsequently integrated within several existing medical image registration frameworks relying on concepts such as B-splines (Rohlfing et al 2003, Yin et al 2009, Wilczewska et al 2017, demons (Mansi et al 2011, Xing et al 2017 or variationals (Haber & Modersitzki 2004, Haber & Modersitzki 2006. However, while this generally led to an improved anatomical plausibility of the estimated deformations, in some cases it also implied an increase in the number of algorithm control parameters and/or computational time, hampering their application for online/real-time imageguided cancer therapies.…”

Section: Introductionmentioning

confidence: 99%

“…A broad range of these methods were also adopted in the medical image registration domain (Maintz and Viergever 1998, Hill et al 2001, Zitová and Flusser 2003, Brock et al 2010, Mani and Arivazhagan 2013, Sotiras et al 2013. A category of registration methods particularly suitable for medical image registration are variational methods (Weickert et al 2003). This is due to their fast numerical schemes, low number of input parameters and their capability of estimating dense and elastic deformations.…”

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confidence: 99%

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Anatomically plausible models and quality assurance criteria for online mono- and multi-modal medical image registration

et al. 2018

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Medical imaging is currently employed in the diagnosis, planning, delivery and response monitoring of cancer treatments. Due to physiological motion and/or treatment response, the shape and location of the pathology and organs-at-risk may change over time. Establishing their location within the acquired images is therefore paramount for an accurate treatment delivery and monitoring. A feasible solution for tracking anatomical changes during an image-guided cancer treatment is provided by image registration algorithms. Such methods are, however, often built upon elements originating from the computer vision/graphics domain. Since the original design of such elements did not take into consideration the material properties of particular biological tissues, the anatomical plausibility of the estimated deformations may not be guaranteed. In the current work we adapt two existing variational registration algorithms, namely Horn-Schunck and EVolution, to online soft tissue tracking. This is achieved by enforcing an incompressibility constraint on the estimated deformations during the registration process. The existing and the modified registration methods were comparatively tested against several quality assurance criteria on abdominal in vivo MR and CT data. These criteria included: the Dice similarity coefficient (DSC), the Jaccard index, the target registration error (TRE) and three additional criteria evaluating the anatomical plausibility of the estimated deformations. Results demonstrated that both the original and the modified registration methods have similar registration capabilities in high-contrast areas, with DSC and Jaccard index values predominantly in the 0.8-0.9 range and an average TRE of 1.6-2.0 mm. In contrast-devoid regions of the liver and kidneys, however, the three additional quality assurance criteria have indicated a considerable improvement of the anatomical plausibility of the deformations estimated by the incompressibility-constrained methods. Moreover, the proposed registration models maintain the potential of the original methods for online image-based guidance of cancer treatments.

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Section: Introductionmentioning

confidence: 99%

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Anatomically plausible models and quality assurance criteria for online mono- and multi-modal medical image registration

et al. 2018

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“…The displacements between consecutive image frames were calculated using a B-spline based elastic registration algorithm 46 in an implementation used in previously conducted researches. 35,47…”

Section: Methodsmentioning

confidence: 99%

“…A range of values of ω s were tested in a previous study. 47 Additionally, for this study the combinations of ω s ranging from 0 to 0.1 and k ω c ranging from 0 to 0.3 were tested on data with reference masks. As a result, values of 0.03 and 0.2 were chosen for ω s and k ω c respectively.…”

Section: Methodsmentioning

confidence: 99%

Segmentation Enhanced Elastic Image Registration for 2D Speckle Tracking Echocardiography—Performance Study In Silico

2022

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Although the two dimensional Speckle Tracking Echocardiography has gained a strong position among medical diagnostic techniques in cardiology, it still requires further developments to improve its repeatability and reliability. Few works have attempted to incorporate the left ventricle segmentation results in the process of displacements and strain estimation to improve its performance. We proposed the use of mask information as an additional penalty in the elastic image registration based displacements estimation. This approach was studied using a short axis view synthetic echocardiographic data, segmented using an active contour method. The obtained masks were distorted to a different degree, using different methods to assess the influence of the segmentation quality on the displacements and strain estimation process. The results of displacements and circumferential strain estimations show, that even though the method is dependent on the mask quality, the potential loss in accuracy due to the poor segmentation quality is much lower than the potential accuracy gain in cases where the segmentation performs well.

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Quantitative Assessment of the Effect of the Out-of-Plane Movement of the Homogenous Ellipsoidal Model of the Left Ventricle on the Deformation Measures Estimated Using 2-D Speckle Tracking—An In-Silico Study

Żmigrodzki

Cygan

Wilczewska

et al. 2018

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Effect of the out-of-plane (OOP) movement amplitude on estimates of global displacements (radial, circumferential) and strains (radial , circumferential ) was studied in an ellipsoidal model of the left ventricle using finite-element modeling (FEM), synthetic ultrasonic data, and short-axis view. This effect was assessed using median of the absolute relative error (RE) of the global parameters. FEM provided node displacements for synthetic ultrasonic data and reference data generation. Displacements were estimated using block-matching (BM) and B-spline (BS) methods. FEM-derived data analysis, free from errors resulting from speckle tracking, indicated that the tissue motion introduced REs of global strain estimates below 4.5%. The effect of the OOP motion amplitude on strain estimates was strain specific and depended on the displacement estimation method. In the case of , the increase of the OOP amplitude resulted in quasi-linear increase of the RE from approximately 10% to 15%. The modulus of the end-systolic (ES) errors of the estimates almost linearly increased with increasing OOP amplitude approximately from 10% to 16%. REs of the estimate were close to 80% and 40%, respectively, in the case of the BM and BS methods, and increased with increasing OOP amplitude. The modulus of the ES errors of the estimates in the case of the BS method was about -40% and showed low sensitivity to the OOP amplitude; in the BM case, these errors varied approximately from -70% to -58% for OOP amplitude from 0 to 15 mm.

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Displacement Field Estimation for Echocardiography Strain Imaging Using B-Spline Based Elastic Image Registration—Synthetic Data Study

Cited by 3 publications

References 11 publications

Anatomically plausible models and quality assurance criteria for online mono- and multi-modal medical image registration

Anatomically plausible models and quality assurance criteria for online mono- and multi-modal medical image registration

Segmentation Enhanced Elastic Image Registration for 2D Speckle Tracking Echocardiography—Performance Study In Silico

Quantitative Assessment of the Effect of the Out-of-Plane Movement of the Homogenous Ellipsoidal Model of the Left Ventricle on the Deformation Measures Estimated Using 2-D Speckle Tracking—An In-Silico Study

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