Download or read book Deformable Registration Techniques for Thoracic CT Images written by Ali Imam Abidi and published by Springer. This book was released on 2020-05-30 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on novel approaches for thoracic computed tomography (CT) image registration and determination of respiratory motion models in a range of patient scenarios. It discusses the use of image registration processes to remove the inconsistencies between medical images acquired using different devices. In the context of comparative research and medical analysis, these methods are of immense value in image registration procedures, not just for thoracic CT images, but for all types of medical images in multiple modalities, and also in establishing a mean respiration motion model. Combined with advanced techniques, the methods proposed have the potential to advance the field of computer vision and help improve existing methods. The book is a valuable resource for those in the scientific community involved in modeling respiratory motion for a large number of people.

Download or read book Registration Methods for Pulmonary Image Analysis written by Alexander Schmidt-Richberg and published by Springer Science & Business Media. This book was released on 2014-01-28 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Various applications in the field of pulmonary image analysis require a registration of CT images of the lung. For example, a registration-based estimation of the breathing motion is employed to increase the accuracy of dose distribution in radiotherapy. Alexander Schmidt-Richberg develops methods to explicitly model morphological and physiological knowledge about respiration in algorithms for the registration of thoracic CT images. The author focusses on two lung-specific issues: on the one hand, the alignment of the interlobular fissures and on the other hand, the estimation of sliding motion at the lung boundaries. He shows that by explicitly considering these aspects based on a segmentation of the respective structure, registration accuracy can be significantly improved.

Download or read book Medical Image Registration written by Joseph V. Hajnal and published by CRC Press. This book was released on 2001-06-27 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image registration is the process of systematically placing separate images in a common frame of reference so that the information they contain can be optimally integrated or compared. This is becoming the central tool for image analysis, understanding, and visualization in both medical and scientific applications. Medical Image Registration provid

Download or read book Adaptive Radiation Therapy written by X. Allen Li and published by CRC Press. This book was released on 2011-01-27 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern medical imaging and radiation therapy technologies are so complex and computer driven that it is difficult for physicians and technologists to know exactly what is happening at the point-of-care. Medical physicists responsible for filling this gap in knowledge must stay abreast of the latest advances at the intersection of medical imaging an

Download or read book Deformable Lung Registration for Pulmonary Image Analysis of MRI and CT Scans written by Mattias Paul Heinrich and published by . This book was released on 2013 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deformable Registration of Multi modal Data Including Rigid Structures written by and published by . This book was released on 2003 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-modality imaging studies are becoming more widely utilized in the analysis of medical data. Anatomical data from CT and MRI are useful for analyzing or further processing functional data from techniques such as PET and SPECT. When data are not acquired simultaneously, even when these data are acquired on a dual-imaging device using the same bed, motion can occur that requires registration between the reconstructed image volumes. As the human torso can allow non-rigid motion, this type of motion should be estimated and corrected. We report a deformation registration technique that utilizes rigid registration for bony structures, while allowing elastic transformation of soft tissue to more accurately register the entire image volume. The technique is applied to the registration of CT and MR images of the lumbar spine. First a global rigid registration is performed to approximately align features. Bony structures are then segmented from the CT data using semi-automated process, and bounding boxes for each vertebra are established. Each CT subvolume is then individually registered to the MRI data using a piece-wise rigid registration algorithm and a mutual information image similarity measure. The resulting set of rigid transformations allows for accurate registration of the parts of the CT and MRI data representing the vertebrae, but not the adjacent soft tissue. To align the soft tissue, a smoothly-varying deformation is computed using a thin platespline(TPS) algorithm. The TPS technique requires a sparse set of landmarks that are to be brought into correspondence. These landmarks are automatically obtained from the segmented data using simple edge-detection techniques and random sampling from the edge candidates. A smoothness parameter is also included in the TPS formulation for characterization of the stiffness of the soft tissue. Estimation of an appropriate stiffness factor is obtained iteratively by using the mutual information cost function on the result of the global deformable transformation.

Download or read book Registration and Recognition in Images and Videos written by Roberto Cipolla and published by Springer. This book was released on 2013-11-19 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout. The International Computer Vision Summer School - ICVSS was established in 2007 to provide both an objective and clear overview and an in-depth analysis of the state-of-the-art research in Computer Vision. The courses are delivered by world renowned experts in the field, from both academia and industry and cover both theoretical and practical aspects of real Computer Vision problems. The school is organized every year by University of Cambridge (Computer Vision and Robotics Group) and University of Catania (Image Processing Lab). Different topics are covered each year. This edited volume contains a selection of articles covering some of the talks and tutorials held during the last editions of the school. The chapters provide an in-depth overview of challenging areas with key references to the existing literature.

Download or read book 4D Modeling and Estimation of Respiratory Motion for Radiation Therapy written by Jan Ehrhardt and published by Springer Science & Business Media. This book was released on 2013-05-30 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book The ITK Software Guide written by Luis Ibáñez and published by . This book was released on 2003 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Image Processing in Radiation Therapy written by Kristy K. Brock and published by CRC Press. This book was released on 2013-08-06 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Images from CT, MRI, PET, and other medical instrumentation have become central to the radiotherapy process in the past two decades, thus requiring medical physicists, clinicians, dosimetrists, radiation therapists, and trainees to integrate and segment these images efficiently and accurately in a clinical environment. Image Processing in Radiation Therapy presents an up-to-date, detailed treatment of techniques and algorithms for the registration, segmentation, reconstruction, and evaluation of imaging data. It describes how these tools are used in radiation planning, treatment delivery, and outcomes assessment. The book spans deformable registration, segmentation, and image reconstruction and shows how to incorporate these practices in radiation therapy. The first section explores image processing in adaptive radiotherapy, online monitoring and tracking, dose accumulation, and accuracy assessment. The second section describes the mathematical approach to deformable registration. The book presents similarity metrics used for registration techniques, discussing their effectiveness and applicability in radiation therapy. It also evaluates parametric and nonparametric image registration techniques and their applications in radiation therapy processes. The third section assesses the efficiency, robustness, and breadth of application of image segmentation approaches, including atlas-based, level set, and registration-based techniques. The fourth section focuses on advanced imaging techniques for radiotherapy, such as 3D image reconstruction and image registration using a graphics processor unit. With contributions from an international group of renowned authors, this book provides a comprehensive description of image segmentation and registration, in-room imaging, and advanced reconstruction techniques. Through many practical examples, it illustrates the clinical rationale and implementation of the techniques.

Download or read book Optimisation and Performance Evaluation in Image Registration Techniques written by and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this research, image registration of lung CT scans and brain T1 MRI images were carried out using regular step gradient descent and one to one evolutionary optimisers, and mean squared error and mutual information as similarity metrics. Performance evaluation was done on the two techniques and a comparison done with existing research. Recent research in image registration techniques has demonstrated its worth in a variety of fields from remote sensing to medical imaging. Image registration methods consist of having two input images named as scene and model being made of points. Registration transformation was then done, which relates the two images and similarity metric function that aims to measure a qualitative value of closeness or degree of fitting between the transformed scene image and the model image. Finally, an optimiser which seeks the optimal transformation inside the defined solution search space was performed. The main objective of this research was to apply optimisation methods in image registration techniques in order to provide the user with an estimate as to how accurate the registration actually was. The specific objectives was to determine the transformation model, the similarity metrics in image registration and carry out a careful validation of performance in registration using known basic error classes and methods for measuring registration accuracy and robustness. The main contribution of this research was the significant improvement achieved in image registration when using regular step gradient descent optimisation as shown by the performance evaluation results. The results of structural similarity index values were consistent and very promising, with values close to 1. This was in conformity with theoretical methods and applications. Registration accuracies attained were influenced by the registration techniques chosen.

Download or read book MRI for Radiotherapy written by Gary Liney and published by Springer. This book was released on 2019-06-20 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides, for the first time, a unified approach to the application of MRI in radiotherapy that incorporates both a physics and a clinical perspective. Readers will find detailed information and guidance on the role of MRI in all aspects of treatment, from dose planning, with or without CT, through to response assessment. Extensive coverage is devoted to the latest technological developments and emerging options. These include hybrid MRI treatment systems, such as MRI-Linac and proton-guided systems, which are ushering in an era of real-time MRI guidance. The past decade has witnessed an unprecedented rise in the use of MRI in the radiation treatment of cancer. The development of highly conformal dose delivery techniques has led to a growing need to harness advanced imaging for patient treatment. With its flexible soft tissue contrast and ability to acquire functional information, MRI offers advantages at all stages of treatment. In documenting the state of the art in the field, this book will be of value to a wide range of professionals. The authors are international experts drawn from the scientific committee of the 2017 MR in RT symposium and the faculty of the ESTRO teaching course on imaging for physicists.

Download or read book High Performance Deformable Image Registration Algorithms for Manycore Processors written by James Shackleford and published by Newnes. This book was released on 2013-06-28 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans. - Demonstrates how to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithms - Shows how to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUs - Provides Programming "tricks" that can help readers develop other image processing algorithms, including registration algorithms for the GPU

Download or read book An Investigation of NURBS based Deformable Image Registration written by Travis James Jacobson and published by . This book was released on 2014 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deformable image registration (DIR) is an essential tool in medical image processing. It provides a means to combine image datasets, allowing for intra-subject, inter-subject, multi-modality, and multi-instance analysis, as well as motion detection and compensation. One of the most popular DIR algorithms models the displacement vector field (DVF) as B-splines, a sum of piecewise polynomials with coefficients that enable local shape control. B-splines have many advantageous properties in the context of DIR, but they often struggle to adequately model steep local gradients and discontinuities. This dissertation addresses that limitation by proposing the replacement of conventional B-splines with a generalized formulation known as a Non-Uniform Rational B-Splines (NURBS). Beginning with the 1D fitting, heuristic rules are developed to determine the values of the additional free parameters introduced by NURBS. These rules are subsequently modified and extended to the 2D and 3D fitting of anonymized and publicly available patient DVFs. Based on the lessons learned from these increasingly complex test cases, a 2D DIR scheme is developed and tested on slices from a thoracic computed tomography (CT) scan. Finally, an automatic, non-uniform scheme is presented, and its registration performance is compared to the conventional uniform methods.

Download or read book Applications of Deformable Image Registration written by Marc Morcos and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The contents of this thesis are best divided into two components: (i) evaluation of atlas-based segmentation and deformable contour propagation and (ii) adaptive radiation therapy using deformable electron density mapping. The first component of this thesis involves the evaluation of two commercial deformable registration systems with respect to automatic segmentation techniques. Overall, the techniques revealed that manual modifications would be required if the structures were to be used for treatment planning. The automatic segmentation methods utilized by both commercial products serve as an excellent starting point for contouring process and also reduce inter- and intra-physician variability when contouring. In the second component, we developed a framework for dose accumulation adaptive radiation therapy. By registering the planning computed tomography (CT) images to the weekly cone-beam computed tomography (CBCT) images, we were able to produce modified CBC...

Download or read book Thoracic Image Analysis written by Jens Petersen and published by Springer. This book was released on 2020-11-04 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the Second International Workshop on Thoracic Image Analysis, TIA 2020, held in Lima, Peru, in October 2020. Due to COVID-19 pandemic the conference was held virtually. COVID-19 infection has brought a lot of attention to lung imaging and the role of CT imaging in the diagnostic workflow of COVID-19 suspects is an important topic. The 14 full papers presented deal with all aspects of image analysis of thoracic data, including: image acquisition and reconstruction, segmentation, registration, quantification, visualization, validation, population-based modeling, biophysical modeling (computational anatomy), deep learning, image analysis in small animals, outcome-based research and novel infectious disease applications.

Download or read book Novel Techniques for Registration of Multimodal Medical Images written by Nima Masoumi and published by . This book was released on 2018 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical image registration is a critical image processing task in many applications such as image-guided surgery (IGS) and image-guided radiotherapy. Herein, a novel automatic inter-modal affine registration technique is proposed based on the correlation ratio (CR) similarity metric firstly. The technique is demonstrated through registering intra-operative ultrasound (US) scans with magnetic resonance (MR) images of 22 patients from a publicly available database. By using landmark-based mean target registration errors (mTRE) for evaluation, the technique has achieved a result of 2.79$\pm$1.13 mm from an initial value of 5.40$\pm$4.31 mm. A nonparametric statistical analysis performed using the Wilcoxon rank sum test shows that there is a significant difference between pre- and post-registration mTREs with a $p$-value of $0.0058$. To achieve this result, the MRI was deemed as the fix image ($I_f$) and the US as the moving image ($I_m$) and then $I_m$ was transformed to align with $I_f$. Covariance matrix adaptation evolutionary strategy (CMA-ES) was utilized to find the optimal affine transformation in registration of $I_m$ to $I_f$. In addition to quantitative validation using mTRE, the results were validated qualitatively by overlaying pre- and post-registration US and MRI to allow visual assessment of the alignment. The proposed fully automatic registration method significantly improved the alignment of MRI and US images and can therefore be used to aid neurosurgeons in resection of brain tumors. In addition to proposing new methods for registration of US and MRI, three different datasets of corresponding CT and US images of vertebrae were collected and presented. In the first dataset, two human patients' lumbar vertebrae are presented and the US images are simulated from the CT images. The second dataset includes corresponding CT and US images of a phantom, made of post-mortem canine cervical and thoracic vertebrae. The third dataset includes the CT and US images of a lamb's lumbar vertebrae. For the two latter datasets, 15 corresponding landmarks were provided and fiducial registration of the corresponding images was performed to acquire a silver standard ground truth of the registration. This dataset will be released online to allow validation of US-CT registration techniques.