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Author: William J. Mullally Publisher: ISBN: Category : Languages : en Pages : 180
Book Description
Abstract: This thesis arises out of the study of lung physiology and the development of new techniques to help analyze the complex and prodigious amount data which modem medical imaging can provide. This document describes work in two major directions. The first is an investigation into which airways in the human airway tree contribute to the decrease in lung function in asthmatics. This works pulls together a number of well understood methods in image analysis and image registration with image data on ventilation defects and methods for building computation models of the human airway tree. We show how to incorporate ventilation defects observed in image data into subject specific models of the human airway tree. Our study indicates that ventilation defects may be caused by closures of larger airways than previously reported. Our second effort has been to advance the field of image registration to solve image alignment problems presented in the study of acute respiratory distress syndrome (ARDS). This has led us to develop two novel image registration techniques: an approach for cost-switching in non-rigid image registration and an approach to image registration using classifiers learned from example images. Our cost-switching approach has led to the first accurate semi-automatic non-rigid registration of images of healthy lungs to those of lungs after the onset of ARDS. Our example-based approach uses multiple classifiers to achieve rigid registration when image appearance has changed dramatically and non-uniformly. We show a significant increase in registration accuracy in comparison to an approach using mutual information.
Author: William J. Mullally Publisher: ISBN: Category : Languages : en Pages : 180
Book Description
Abstract: This thesis arises out of the study of lung physiology and the development of new techniques to help analyze the complex and prodigious amount data which modem medical imaging can provide. This document describes work in two major directions. The first is an investigation into which airways in the human airway tree contribute to the decrease in lung function in asthmatics. This works pulls together a number of well understood methods in image analysis and image registration with image data on ventilation defects and methods for building computation models of the human airway tree. We show how to incorporate ventilation defects observed in image data into subject specific models of the human airway tree. Our study indicates that ventilation defects may be caused by closures of larger airways than previously reported. Our second effort has been to advance the field of image registration to solve image alignment problems presented in the study of acute respiratory distress syndrome (ARDS). This has led us to develop two novel image registration techniques: an approach for cost-switching in non-rigid image registration and an approach to image registration using classifiers learned from example images. Our cost-switching approach has led to the first accurate semi-automatic non-rigid registration of images of healthy lungs to those of lungs after the onset of ARDS. Our example-based approach uses multiple classifiers to achieve rigid registration when image appearance has changed dramatically and non-uniformly. We show a significant increase in registration accuracy in comparison to an approach using mutual information.
Author: Krishnan B. Chandran Publisher: Springer Science & Business Media ISBN: 1441973508 Category : Technology & Engineering Languages : en Pages : 474
Book Description
Image-Based Computational Modeling of the Human Circulatory and Pulmonary Systems provides an overview of the current modeling methods and applications enhancing interventional treatments and computer-aided surgery. A detailed description of the techniques behind image acquisition, processing and three-dimensional reconstruction are included. Techniques for the computational simulation of solid and fluid mechanics and structure interaction are also discussed, in addition to various cardiovascular and pulmonary applications. Engineers and researchers involved with image processing and computational modeling of human organ systems will find this a valuable reference.
Author: Ayman El-Baz Publisher: CRC Press ISBN: 1439845573 Category : Medical Languages : en Pages : 483
Book Description
Lung cancer remains the leading cause of cancer-related deaths worldwide. Early diagnosis can improve the effectiveness of treatment and increase a patient’s chances of survival. Thus, there is an urgent need for new technology to diagnose small, malignant lung nodules early as well as large nodules located away from large diameter airways because the current technology—namely, needle biopsy and bronchoscopy—fail to diagnose those cases. However, the analysis of small, indeterminate lung masses is fraught with many technical difficulties. Often patients must be followed for years with serial CT scans in order to establish a diagnosis, but inter-scan variability, slice selection artifacts, differences in degree of inspiration, and scan angles can make comparing serial scans unreliable. Lung Imaging and Computer Aided Diagnosis brings together researchers in pulmonary image analysis to present state-of-the-art image processing techniques for detecting and diagnosing lung cancer at an early stage. The book addresses variables and discrepancies in scans and proposes ways of evaluating small lung masses more consistently to allow for more accurate measurement of growth rates and analysis of shape and appearance of the detected lung nodules. Dealing with all aspects of image analysis of the data, this book examines: Lung segmentation Nodule segmentation Vessels segmentation Airways segmentation Lung registration Detection of lung nodules Diagnosis of detected lung nodules Shape and appearance analysis of lung nodules Contributors also explore the effective use of these methodologies for diagnosis and therapy in clinical applications. Arguably the first book of its kind to address and evaluate image-based diagnostic approaches for the early diagnosis of lung cancer, Lung Imaging and Computer Aided Diagnosis constitutes a valuable resource for biomedical engineers, researchers, and clinicians in lung disease imaging.
Author: Nathan David Ellingwood Publisher: ISBN: Category : Algorithms Languages : en Pages : 103
Book Description
Though parallelization was straightforward, the complex geometry of the lungs and use of an unstructured mesh provided challenges that were addressed by the GPU methods. The results of the GPU methods were tested for various numbers of particles and compared to a previously validated single-threaded CPU version and demonstrated dramatic speedup over the single-threaded CPU version and 12-threaded CPU versions.
Author: Alexander Schmidt-Richberg Publisher: Springer Science & Business Media ISBN: 3658016620 Category : Computers Languages : en Pages : 179
Book Description
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.
Author: Paolo Di Giamberardino Publisher: CRC Press ISBN: 0203075374 Category : Computers Languages : en Pages : 496
Book Description
Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III contains all contributions presented at the International Symposium CompIMAGE 2012 - Computational Modelling of Object Presented in Images: Fundamentals, Methods and Applications (Rome, Italy, 5-7 September 2012). The contributions cover the state-o
Author: Ayman El-Baz Publisher: CRC Press ISBN: 1439845581 Category : Medical Languages : en Pages : 473
Book Description
Lung cancer remains the leading cause of cancer-related deaths worldwide. Early diagnosis can improve the effectiveness of treatment and increase a patient's chances of survival. Thus, there is an urgent need for new technology to diagnose small, malignant lung nodules early as well as large nodules located away from large diameter airways because
Author: Guanglei Xiong Publisher: Stanford University ISBN: Category : Languages : en Pages : 134
Book Description
Modern anatomical medical imaging technologies, such as computed tomography and magnetic resonance, capture structures of the human body in exquisite detail. Computational anatomy is a developing discipline to extract and characterize the anatomy from images. Unfortunately, anatomical images do not reveal the functional behavior. Computational physiology shows great potential to link the structure-function relationship by considering both the anatomical information and the physical governing laws. The simulated physiology can be used to assess physiological states, and more importantly predict the outcomes of interventions. On the other hand, advances in the functional imaging techniques provide measured physiology information and should be utilized together with computational physiology. In the theme of computational anatomy and physiology, this dissertation describes computational methods of modeling vascular geometry for image-based blood flow computation and tracking pulmonary motion for image-guided radiation therapy. Blood flow computation is a useful tool to quantify in vivo hemodynamics. The essential first step is to model vascular geometry from medical imaging data. I have developed a new workflow for this task. The geometric model construction is based on 3D image segmentation and geometric processing. To represent the topology of the constructed model, I have developed a novel centerline extraction method. To account for compliant vessels, methods to assign spatially-varying mechanical properties of the vessel wall are also developed. The workflow greatly increases the modeling efficiency. The combination of the patient-specific geometry and wall deformation can enhance the fidelity of blood flow simulation. Image-based blood flow computation also holds great promise for device design and surgical procedure evaluation. Next, I have developed novel virtual intervention methods to deploy stents or stent grafts to patient-specific pre-operative geometric models constructed from medical images. These methods enable prospective model construction and may be used to evaluate the outcomes of alternative treatment options. Respiratory motion is closely related to the physiology of the lung. Finally, I have developed a novel framework to track patient-specific pulmonary motion from 4D computed tomography images. A large set of vascular junction structures in the lung are identified as landmarks and tracked to obtain their motion trajectories. This framework can provide accurate motion information, which is important in radiation therapy to reduce healthy tissue irradiation while allowing target dose escalation. This work demonstrates the importance of the geometry and motion modeling tools in computational anatomy and physiology. Accurate physiological information, whether simulated or measured, will benefit the diagnosis and treatment of various diseases.
Author: S. Prabha Publisher: CRC Press ISBN: 1000439372 Category : Medical Languages : en Pages : 144
Book Description
The aim of this book is to present new computational techniques and methodologies for the analysis of the clinical, epidemiological and public health aspects of SARS-CoV-2 and COVID-19 pandemic. The book presents the use of soft computing techniques such as machine learning algorithms for analysis of the epidemiological aspects of the SARS-CoV-2. This book clearly explains novel computational image processing algorithms for the detection of COVID-19 lesions in lung CT and X-ray images. It explores various computational methods for computerized analysis of the SARS-CoV-2 infection including severity assessment. The book provides a detailed description of the algorithms which can potentially aid in mass screening of SARS-CoV-2 infected cases. Finally the book also explains the conventional epidemiological models and machine learning techniques for the prediction of the course of the COVID-19 epidemic. It also provides real life examples through case studies. The book is intended for biomedical engineers, mathematicians, postgraduate students; researchers; medical scientists working on identifying and tracking infectious diseases.
Author: William J. Mullally
Author: William J. Mullally
Author: Krishnan B. Chandran
Author: Ayman El-Baz
Author: Nathan David Ellingwood
Author: Matthias Ochs
Author: Alexander Schmidt-Richberg
Author: Paolo Di Giamberardino
Author: Ayman El-Baz
Author: Guanglei Xiong
Author: S. Prabha