Respiratory Motion Compensation in Emission Tomography PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Respiratory Motion Compensation in Emission Tomography PDF full book. Access full book title Respiratory Motion Compensation in Emission Tomography by Mauricio Antonio Reyes Aguirre. Download full books in PDF and EPUB format.
Author: Mauricio Antonio Reyes Aguirre Publisher: ISBN: Category : Languages : en Pages : 300
Book Description
This thesis work deals with the problem of respiratory motion correction in emission tomography. It has been proven that respiratory motion renders blurred reconstructed images, affecting lesions detection, diagnosis, treatment, etc. The proposed approach was designed to work without any external tracking devices. It presents a retrospective scheme of motion correction based on a motion model plugged to the image reconstruction step. The model takes into account displacements and elastic deformations of emission elements (voxels), which allows to consider the non-rigid deformations produced in the thorax during respiration. Furthermore, the chosen voxel modeling improves computations, outperforming classical methods of voxel/detector-tube. Two estimation models were investigated and developed. A first simplified model consists on adapting a known respiratory motion model, obtained from a single subject, to the patient anatomy. The initial known model describes by means of a displacement vector field, the lungs deformations produced between extremal respiratory states. This displacement vector field is further adapted by means of an affine transformation to the patient's anatomy, yielding a displacement vector field that matches the thoracic cavity of the patient . The second method deals with the possible lack of robustness caused by the fact of using a single subject when constructing the known displacement vector field of the simplified method. Incorporation of subject variability into a statistical respiratory motion model was developed. The whole methodology was developed under a 3D framework and tested against simulated and real data.
Author: Mauricio Antonio Reyes Aguirre Publisher: ISBN: Category : Languages : en Pages : 300
Book Description
This thesis work deals with the problem of respiratory motion correction in emission tomography. It has been proven that respiratory motion renders blurred reconstructed images, affecting lesions detection, diagnosis, treatment, etc. The proposed approach was designed to work without any external tracking devices. It presents a retrospective scheme of motion correction based on a motion model plugged to the image reconstruction step. The model takes into account displacements and elastic deformations of emission elements (voxels), which allows to consider the non-rigid deformations produced in the thorax during respiration. Furthermore, the chosen voxel modeling improves computations, outperforming classical methods of voxel/detector-tube. Two estimation models were investigated and developed. A first simplified model consists on adapting a known respiratory motion model, obtained from a single subject, to the patient anatomy. The initial known model describes by means of a displacement vector field, the lungs deformations produced between extremal respiratory states. This displacement vector field is further adapted by means of an affine transformation to the patient's anatomy, yielding a displacement vector field that matches the thoracic cavity of the patient . The second method deals with the possible lack of robustness caused by the fact of using a single subject when constructing the known displacement vector field of the simplified method. Incorporation of subject variability into a statistical respiratory motion model was developed. The whole methodology was developed under a 3D framework and tested against simulated and real data.
Author: Tzu-Cheng Lee Publisher: ISBN: Category : Languages : en Pages : 153
Book Description
Positron emission tomography (PET) is a commonly used imaging tool in the management of patients with lung cancer and is of considerable interest in quantitative imaging of the thorax. Mismatch of PET data with computed tomography (CT) attenuation correction (CTAC) due to respiratory motion is a known source of errors in PET imaging. In theory, this can be corrected by matching individual PET and CT phases which have been generated by respiratory-correlated PET and CT. However, due to the high variability of patient breathing patterns and the nature of the scanning time differences between PET and CT, current respiratory-gated CTAC protocols for the irregular breather may cause additional bias in the PET image values. A ten-fold extension of the CT scanning time duration helps reduce PET imaging bias, but leads to the higher radiation dose to the patient. Lowering the CT source flux level to reduce dose, however, leads to increased noise and bias. Here we test the possibility of using model based iterative reconstruction algorithms (MBIRs) for generating the sparse-view, ultra-low-dose (i.e. an order lower than current low-dose protocols) CTAC images for both phantom and patient PET data. We also propose a new variance estimation model, which considers statistical changes caused by the non-positivity correction process, for the MBIR algorithms. The model based iterative CT reconstruction approach does generate more accurate CTAC map compared to current approaches. However, since iterative reconstruction algorithms typically assume a normal distribution of the attenuation data, we tested if the assumption is still valid in the ultra-low-dose regime. The simulation and empirical ultra-low-dose CT studies showed a skewed post-log likelihood distribution in certain ranges. The information delineates the estimation limits of model based iterative reconstruction approach on the ultra-low-dose CT imaging, and potentially helps guide scanning protocols customized for a lowest-reasonable radiation dose.
Author: Fabian Gigengack Publisher: Springer ISBN: 3319083929 Category : Computers Languages : en Pages : 98
Book Description
Respiratory and cardiac motion leads to image degradation in Positron Emission Tomography (PET), which impairs quantification. In this book, the authors present approaches to motion estimation and motion correction in thoracic PET. The approaches for motion estimation are based on dual gating and mass-preserving image registration (VAMPIRE) and mass-preserving optical flow (MPOF). With mass-preservation, image intensity modulations caused by highly non-rigid cardiac motion are accounted for. Within the image registration framework different data terms, different variants of regularization and parametric and non-parametric motion models are examined. Within the optical flow framework, different data terms and further non-quadratic penalization are also discussed. The approaches for motion correction particularly focus on pipelines in dual gated PET. A quantitative evaluation of the proposed approaches is performed on software phantom data with accompanied ground-truth motion information. Further, clinical applicability is shown on patient data. The book concludes with an outlook of recent developments and potential future advances in the field of PET motion correction.
Author: Jan Ehrhardt Publisher: Springer Science & Business Media ISBN: 3642364411 Category : Science Languages : en Pages : 352
Book Description
Respiratory motion causes an important uncertainty in radiotherapy planning of the thorax and upper abdomen. The main objective of radiation therapy is to eradicate or shrink tumor cells without damaging the surrounding tissue by delivering a high radiation dose to the tumor region and a dose as low as possible to healthy organ tissues. Meeting this demand remains a challenge especially in case of lung tumors due to breathing-induced tumor and organ motion where motion amplitudes can measure up to several centimeters. Therefore, modeling of respiratory motion has become increasingly important in radiation therapy. With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient’s body. Furthermore, image registration enables the estimation of the breathing-induced motion and the description of the temporal change in position and shape of the structures of interest by establishing the correspondence between images acquired at different phases of the breathing cycle. In radiation therapy these motion estimations are used to define accurate treatment margins, e.g. to calculate dose distributions and to develop prediction models for gated or robotic radiotherapy. In this book, the increasing role of image registration and motion estimation algorithms for the interpretation of complex 4D medical image sequences is illustrated. Different 4D CT image acquisition techniques and conceptually different motion estimation algorithms are presented. The clinical relevance is demonstrated by means of example applications which are related to the radiation therapy of thoracic and abdominal tumors. The state of the art and perspectives are shown by an insight into the current field of research. The book is addressed to biomedical engineers, medical physicists, researchers and physicians working in the fields of medical image analysis, radiology and radiation therapy.
Author: Mohammad Dawood Publisher: CRC Press ISBN: 1439812985 Category : Medical Languages : en Pages : 304
Book Description
Written by an interdisciplinary team of medical doctors, computer scientists, physicists, engineers, and mathematicians, Correction Techniques in Emission Tomography presents various correction methods used in emission tomography to generate and enhance images. It discusses the techniques from a computer science, mathematics, and physics viewpoint. The book gives a comprehensive overview of correction techniques at different levels of the data processing workflow. It covers nuclear medicine imaging, hybrid emission tomography (PET-CT, SPECT-CT, PET-MRI, PET-ultrasound), and optical imaging (fluorescence molecular tomography). It illustrates basic principles as well as recent advances, such as model-based iterative algorithms and 4D methods. An important aspect of the book is on new and sophisticated motion correction techniques in PET imaging. These techniques enable high-resolution, high-quality images, leading to better imaging analysis and image-based diagnostics. Reflecting state-of-the-art research, this volume explores the range of problems that occur in emission tomography. It looks at how the resulting images are affected and presents practical compensation methods to overcome the problems and improve the images.
Author: Andrea Martinez-Movilla Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Abstract: Background Patient's breathing affects the quality of chest images acquired with positron emission tomography/computed tomography (PET/CT) studies. Movement correction is required to optimize PET quantification in clinical settings. We present a reproducible methodology to compare the impact of different movement compensation protocols on PET image quality. Static phantom images were set as reference values, and recovery coefficients (RCs) were calculated from motion compensated images for the phantoms in respiratory movement. Image quality was evaluated in terms of: (1) volume accuracy (VA) with the NEMA phantom; (2) concentration accuracy (CA) by six refillable inserts within the electron density CIRS phantom; and (3) spatial resolution (R) with the Jaszczak phantom. Three different respiratory patterns were applied to the phantoms. We developed an open-source package to automatically analyze VA, CA and R. We compared 10 different movement compensation protocols available in the Philips Gemini TF-64 PET/CT (4-, 6-, 8- and 10-time bins, 20%-, 30%-, 40%-window width in Inhale and Exhale). Results The homemade package provided RC values for VA, CA and R of 102 PET images in less than 5 min. Results of the comparison of the 10 different protocols demonstrated the feasibility of the proposed method for quantifying the variations observed qualitatively. Overall, prospective protocols showed better motion compensation than retrospective. The best performance was obtained for the protocol Exhale 30% (0.3 s after maximum Exhale position and window width of 30%) with RCVA=1.6±1.3 , RCCA=0.90±0.09 and RCR=0.6±0.4 . Among retrospective protocols, 8 Phase protocol showed the best performance. Conclusion We provided an open-source package able to automatically evaluate the impact of motion compensation methods on PET image quality. A setup based on commonly available experimental phantoms is recommended. Its application for the comparison of 10 time-based approaches showed that Exhale 30% protocol had the best performance. The proposed framework is not specific to the phantoms and protocols presented on this study
Author: Mauricio Antonio Reyes Aguirre
Author: Mauricio Antonio Reyes Aguirre
Author: Nicole Christine Detorie
Author: Tzu-Cheng Lee
Author: Fabian Gigengack
Author: Nikolaos Dikaios
Author: Mohammad Dawood
Author: Wenjia Bai
Author: Jan Ehrhardt
Author: Mohammad Dawood
Author: Andrea Martinez-Movilla