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Deformable Image Registration

G Guidi, N Maffei, B Meduri, E D'Angelo, G M Mistretta, P Ceroni, A Ciarmatori, A Bernabei, S Maggi, M Cardinali, V E Morabito, F Rosica, S Malara, A Savini, G Orlandi, C D'Ugo, F Bunkheila, M Bono, S Lappi, C Blasi, F Lohr, T Costi
PURPOSE: To predict patients who would benefit from adaptive radiotherapy (ART) and re-planning intervention based on machine learning from anatomical and dosimetric variations in a retrospective dataset. MATERIALS AND METHODS: 90 patients (pts) treated for head-neck cancer (H&N) formed a multicenter data-set. 41 H&N pts (45.6%) were considered for learning; 49 pts (54.4%) were used to test the tool. A homemade machine-learning classifier was developed to analyze volume and dose variations of parotid glands (PG)...
October 17, 2016: Physica Medica: PM
Clément Chesseboeuf
This document presents a non-rigid registration algorithm for the use of brain magnetic resonance (MR) images comparison. More precisely, we want to compare pre-operative and post-operative MR images in order to assess the deformation due to a surgical removal. The proposed algorithm has been studied in Chesseboeuf et al. ((Non-rigid registration of magnetic resonance imaging of brain. IEEE, 385-390. doi: 10.1109/IPTA.2015.7367172 , 2015), following ideas of Trouvé (An infinite dimensional group approach for physics based models in patterns recognition...
October 19, 2016: Acta Biotheoretica
Amy Yuan, Jie Wei, Carl P Gaebler, Hailiang Huang, Devin Olek, Guang Li
PURPOSE: To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. METHODS AND MATERIALS: A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP)...
September 3, 2016: International Journal of Radiation Oncology, Biology, Physics
E Metcalfe, L Aspin, R Speight, E Ermiş, S Ramasamy, K Cardale, K E Dyker, M Sen, R J D Prestwich
AIMS: To determine outcomes after adjuvant radiotherapy for squamous cell carcinoma of the oral cavity and to correlate locoregional recurrence patterns with radiotherapy target volumes. MATERIALS AND METHODS: All patients receiving adjuvant radiotherapy±chemotherapy after surgery with curative intent for oral cavity squamous cell carcinoma between 2007 and 2012 were retrospectively analysed. Locoregional recurrences were reconstructed on the planning computed tomography scan by both deformable image co-registration and by visual assessment...
October 3, 2016: Clinical Oncology: a Journal of the Royal College of Radiologists
J Vickress, J Battista, R Barnett, J Morgan, S Yartsev
Deformable image registration (DIR) has become a common tool in medical imaging across both diagnostic and treatment specialties, but the methods used offer varying levels of accuracy. Evaluation of DIR is commonly performed using manually selected landmarks, which is subjective, tedious and time consuming. We propose a semi-automated method that saves time and provides accuracy comparable to manual selection. Three landmarking methods including manual (with two independent observers), scale invariant feature transform (SIFT), and SIFT with manual editing (SIFT-M) were tested on 10 thoracic 4DCT image studies corresponding to the 0% and 50% phases of respiration...
October 21, 2016: Physics in Medicine and Biology
B Denis de Senneville, C Zachiu, M Ries, C Moonen
Image registration is part of a large variety of medical applications including diagnosis, monitoring disease progression and/or treatment effectiveness and, more recently, therapy guidance. Such applications usually involve several imaging modalities such as ultrasound, computed tomography, positron emission tomography, x-ray or magnetic resonance imaging, either separately or combined. In the current work, we propose a non-rigid multi-modal registration method (namely EVolution: an edge-based variational method for non-rigid multi-modal image registration) that aims at maximizing edge alignment between the images being registered...
October 21, 2016: Physics in Medicine and Biology
Sieun Lee, Nicolas Charon, Benjamin Charlier, Karteek Popuri, Evgeniy Lebed, Marinko V Sarunic, Alain Trouvé, Mirza Faisal Beg
We propose a novel approach for quantitative shape variability analysis in retinal optical coherence tomography images using the functional shape (fshape) framework. The fshape framework uses surface geometry together with functional measures, such as retinal layer thickness defined on the layer surface, for registration across anatomical shapes. This is used to generate a population mean template of the geometry-function measures from each individual. Shape variability across multiple retinas can be measured by the geometrical deformation and functional residual between the template and each of the observations...
September 20, 2016: Medical Image Analysis
Perry Johnson, Kyle R Padgett, Kuan L Chen, Nesrin Dogan
No abstract text is available yet for this article.
2016: Journal of Applied Clinical Medical Physics
Amy Walker, Peter Metcalfe, Gary Liney, Vikneswary Batumalai, Kylie Dundas, Carri Glide-Hurst, Geoff P Delaney, Miriam Boxer, Mei Ling Yap, Jason Dowling, David Rivest-Henault, Elise Pogson, Lois Holloway
The purpose of this study was to determine the impact of magnetic resonance imaging (MRI) geometric distortions when using MRI for target delineation and planning for whole-breast, intensity-modulated radiotherapy (IMRT). Residual system distortions and combined systematic and patient-induced distortions are considered. This retrospective study investigated 18 patients who underwent whole-breast external beam radiotherapy, where both CT and MRIs were acquired for treatment planning. Distortion phantoms were imaged on two MRI systems, dedicated to radiotherapy planning (a wide, closed-bore 3T and an open-bore 1T)...
2016: Journal of Applied Clinical Medical Physics
Jianbing Yi, Hao Yang, Xuan Yang, Guoliang Chen
We propose a deformable registration approach to estimate patient-specific lung motion during free breathing for four-dimensional (4D) computed tomography (CT) based on point matching and tracking between images in different phases. First, a robust point matching (RPM) algorithm coarsely aligns the source phase image onto all other target phase images of 4D CT. Scale-invariant feature transform (SIFT) is introduced into the cost function in order to accelerate and stabilize the convergence of the point matching...
September 20, 2016: Computers in Biology and Medicine
Qianjin Feng, Yujia Zhou, Xueli Li, Yingjie Mei, Zhentai Lu, Yu Zhang, Yanqiu Feng, Yaqin Liu, Wei Yang, Wufan Chen
A technical challenge in the registration of dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging in the liver is intensity variations caused by contrast agents. Such variations lead to the failure of the traditional intensity-based registration method. To address this problem, a manifold-based registration framework for liver DCE-MR time series is proposed. We assume that liver DCE-MR time series are located on a low-dimensional manifold and determine intrinsic similarities between frames. Based on the obtained manifold, the large deformation of two dissimilar images can be decomposed into a series of small deformations between adjacent images on the manifold through gradual deformation of each frame to the template image along the geodesic path...
September 29, 2016: Scientific Reports
M King, G Xiong, P G Maxim, M Diehn, B W Loo, L Xing
No abstract text is available yet for this article.
October 1, 2016: International Journal of Radiation Oncology, Biology, Physics
E E Ahunbay, O Ates, A Li
No abstract text is available yet for this article.
October 1, 2016: International Journal of Radiation Oncology, Biology, Physics
C H Chapman, D Polan, S Jolly, J I Prisciandaro, K K Brock
No abstract text is available yet for this article.
October 1, 2016: International Journal of Radiation Oncology, Biology, Physics
M Tanooka, H Doi, T Ishida, T Wakayama, H Inoue, T Matsumoto, K Tarutani, K Kosaka, N Kamikonya, K Sakamoto
No abstract text is available yet for this article.
October 1, 2016: International Journal of Radiation Oncology, Biology, Physics
Y Guo, J Li, P Zhang, J Wang
No abstract text is available yet for this article.
October 1, 2016: International Journal of Radiation Oncology, Biology, Physics
L E M Wisse, D H Adler, R Ittyerah, J B Pluta, J L Robinson, T Schuck, J Q Trojanowski, M Grossman, J A Detre, M A Elliott, J B Toledo, W Liu, S Pickup, S R Das, D A Wolk, P A Yushkevich
Multiple techniques for quantification of hippocampal subfields from in vivo MRI have been proposed. Linking in vivo MRI to the underlying histology can help validate and improve these techniques. High-resolution ex vivo MRI can provide an intermediate modality to map information between these very different imaging modalities. This article evaluates the ability to match information between in vivo and ex vivo MRI in the same subjects. We perform rigid and deformable registration on 10 pairs of in vivo (3 T, 0...
September 24, 2016: Cerebral Cortex
James Dormer, Xulei Qin, Ming Shen, Silun Wang, Xiaodong Zhang, Rong Jiang, Mary B Wagner, Baowei Fei
Accurate extraction of cardiac fiber orientation from diffusion tensor imaging is important for determining heart structure and function. However, the acquisition of magnetic resonance (MR) diffusion tensor images is costly and time consuming. By comparison, cardiac ultrasound imaging is rapid and relatively inexpensive, but it lacks the capability to directly measure fiber orientations. In order to create a detailed heart model from ultrasound data, a three-dimensional (3D) diffusion tensor imaging (DTI) with known fiber orientations can be registered to an ultrasound volume through a geometric mask...
February 27, 2016: Proceedings of SPIE
Daniel Markel, Ives Levesque, Joe Larkin, Pierre Léger, Issam El Naqa
At present, there exists few openly available methods for evaluation of simultaneous segmentation and registration algorithms. These methods allow for a combination of both techniques to track the tumor in complex settings such as adaptive radiotherapy. We have produced a quality assurance platform for evaluating this specific subset of algorithms using a preserved porcine lung in such that it is multi-modality compatible: positron emission tomography (PET), computer tomography (CT) and magnetic resonance imaging (MRI)...
October 7, 2016: Physics in Medicine and Biology
Lars König, Alexander Derksen, Nils Papenberg, Benjamin Haas
BACKGROUND: Deformable image registration (DIR) is a key component in many radiotherapy applications. However, often resulting deformations are not satisfying, since varying deformation properties of different anatomical regions are not considered. To improve the plausibility of DIR in adaptive radiotherapy in the male pelvic area, this work integrates a local rigidity deformation model into a DIR algorithm. METHODS: A DIR framework is extended by constraints, enforcing locally rigid deformation behavior for arbitrary delineated structures...
2016: Radiation Oncology
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