A Novel Intensity Similarity Metric with Soft Spatial Constraint for a Deformable Image Registration Problem in Radiation Therapy

Khamene, Ali; Zikic, Darko; Diallo, Mamadou Saliou; Boettger, Thomas; Rietzel, Eike

doi:10.1007/978-3-642-04268-3_102

Cited by 4 publications

(1 citation statement)

References 12 publications

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“…Deformable image registration is used to acquire transformation maps 0 M i that establish a relationship between anatomically identical locations of the reference phase and all other phases of the 4D-CT. In our current realization, optimization and application of these transformation maps are performed with vtkCISG (Hartkens 2003), but incorporation of other deformation algorithms (Khamene et al 2009, Shackleford et al 2010 is in preparation. During beam delivery of the treatment plan target motion is measured and divided into phases accordingly.…”

Section: Calculation Of the Rbe-weighted Dosementioning

confidence: 99%

Calculation and experimental verification of the RBE-weighted dose for scanned ion beams in the presence of target motion

Gemmel¹,

Rietzel²,

Kraft³

et al. 2011

Phys. Med. Biol.

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We present an algorithm suitable for the calculation of the RBE-weighted dose for moving targets with a scanned particle beam. For verification of the algorithm, we conducted a series of cell survival measurements that were compared to the calculations. Calculation of the relative biological effectiveness (RBE) with respect to tumor motion was included in the treatment planning procedure, in order to fully assess its impact on treatment delivery with a scanned ion beam. We implemented an algorithm into our treatment planning software TRiP4D which allows determination of the RBE including its dependence on target tissue, absorbed dose, energy and particle spectra in the presence of organ motion. The calculations are based on time resolved computed tomography (4D-CT) and the corresponding deformation maps. The principal of the algorithm is illustrated in in silico simulations that provide a detailed view of the different compositions of the energy and particle spectra at different target positions and their consequence on the resulting RBE. The calculations were experimentally verified with several cell survival measurements using a dynamic phantom and a scanned carbon ion beam. The basic functionality of the new dose calculation algorithm has been successfully tested in in silico simulations. The algorithm has been verified by comparing its predictions to cell survival measurements. Four experiments showed in total a mean difference (standard deviation) of -1.7% (6.3%) relative to the target dose of 9 Gy (RBE). The treatment planning software TRiP is now capable to calculate the patient relevant RBE-weighted dose in the presence of target motion and was verified against cell survival measurements.

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Section: Calculation Of the Rbe-weighted Dosementioning

confidence: 99%

Calculation and experimental verification of the RBE-weighted dose for scanned ion beams in the presence of target motion

Gemmel¹,

Rietzel²,

Kraft³

et al. 2011

Phys. Med. Biol.

View full text Add to dashboard Cite

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Registration of Pre- and Postresection Ultrasound Volumes With Noncorresponding Regions in Neurosurgery

Zhou

Rivaz

2016

IEEE J. Biomed. Health Inform.

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Brain tissue deforms significantly after opening the dura and during tumor resection, invalidating preoperative imaging data. Ultrasound is a popular imaging modality for providing the neurosurgeon with real-time updated images of brain tissue. Interpretation of postresection ultrasound images is difficult due to large brain shift and tissue resection. Furthermore, several factors degrade the quality of postresection ultrasound images such as the strong reflection of waves at the interface of saline water and brain tissue in resection cavities, air bubbles, and the application of blood-clotting agents around the edges of resection. Image registration allows the comparison of postresection ultrasound images with higher quality preresection images, assists in interpretation of postresection images and may help identify residual tumor, and, as such, is of significant clinical importance. In this paper, we propose a nonrigid symmetric registration (NSR) framework for accurate alignment of pre- and postresection volumetric ultrasound images in near real time. We first formulate registration as minimization of a regularized cost function and analytically derive its derivative to efficiently optimize the cost function. An outlier detection algorithm is proposed and utilized in this framework to identify noncorresponding regions (outliers) and therefore improve the robustness and accuracy of registration. We use an efficient second-order minimization method for fast and robust optimization. Furthermore, we exploit a symmetric and inverse-consistent method to generate realistic deformation fields. The results show that NSR significantly improves the quality of the alignment between pre- and postresection ultrasound images.

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Automatic Deformable MR-Ultrasound Registration for Image-Guided Neurosurgery

Rivaz¹,

Chen

Collins

2015

IEEE Trans. Med. Imaging

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In this work, we present a novel algorithm for registration of 3-D volumetric ultrasound (US) and MR using Robust PaTch-based cOrrelation Ratio (RaPTOR). RaPTOR computes local correlation ratio (CR) values on small patches and adds the CR values to form a global cost function. It is therefore invariant to large amounts of spatial intensity inhomogeneity. We also propose a novel outlier suppression technique based on the orientations of the RaPTOR gradients. Our deformation is modeled with free-form cubic B-splines. We analytically derive the derivatives of RaPTOR with respect to the transformation, i.e., the displacement of the B-spline nodes, and optimize RaPTOR using a stochastic gradient descent approach. RaPTOR is validated on MR and tracked US images of neurosurgery. Deformable registration of the US and MR images acquired, respectively, preoperation and postresection is of significant clinical significance, but challenging due to, among others, the large amount of missing correspondences between the two images. This work is also novel in that it performs automatic registration of this challenging dataset. To validate the results, we manually locate corresponding anatomical landmarks in the US and MR images of tumor resection in brain surgery. Compared to rigid registration based on the tracking system alone, RaPTOR reduces the mean initial mTRE over 13 patients from 5.9 to 2.9 mm, and the maximum initial TRE from 17.0 to 5.9 mm. Each volumetric registration using RaPTOR takes about 30 sec on a single CPU core. An important challenge in the field of medical image analysis is the shortage of publicly available dataset, which can both facilitate the advancement of new algorithms to clinical settings and provide a benchmark for comparison. To address this problem, we will make our manually located landmarks available online.

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A Novel Intensity Similarity Metric with Soft Spatial Constraint for a Deformable Image Registration Problem in Radiation Therapy

Cited by 4 publications

References 12 publications

Calculation and experimental verification of the RBE-weighted dose for scanned ion beams in the presence of target motion

Calculation and experimental verification of the RBE-weighted dose for scanned ion beams in the presence of target motion

Registration of Pre- and Postresection Ultrasound Volumes With Noncorresponding Regions in Neurosurgery

Automatic Deformable MR-Ultrasound Registration for Image-Guided Neurosurgery

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