Download or read book Penalized Maximum likelihood PET Image Reconstruction for Lesion Detection written by Li Yang and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Detecting cancerous lesions is one major clinical application of positron emission tomography (PET). Statistical reconstruction methods based on the penalized maximum-likelihood (PML) principle have been developed to improve image quality such as spatial resolution, noise variance, contrast-to-noise ratio, etc. However, these technical metrics do not necessarily reflect the performance of a specific clinical task. In this dissertation, we focus on a task-specific metric to evaluate image quality and optimize PML reconstruction for lesion detection through penalty design, resolution modeling, and dynamic imaging. To assess lesion detectability in 3D images, we develop a multiview channelized Hotelling observer (mvCHO) to mimic the condition where a human observer examines three orthogonal views of a 3D image for detecting lesions. We derive simplified theoretical expressions that allow fast prediction of lesion detectability based on the mvCHO in PML reconstruction. The theoretical results are then applied to guide the design of a shift-variant quadratic penalty function in PML reconstruction to maximize lesion detectability in fully 3D PET. The proposed method is evaluated using computer-based Monte Carlo simulations as well as clinical patient data with superimposed lesions. The second focus of this dissertation is to improve lesion detection through resolution modeling (RM). Incorporating resolution modeling within reconstruction has been shown to improve spatial resolution and tumor contrast, by modeling resolution degrading phenomena such as positron range, inter-crystal scatter and photon non-collinearity. Here we extend our theoretical analysis of the PML reconstruction to quantitatively evaluate the effect of image-space RM on detection performance. We then propose a task-based resolution modeling in PML reconstruction and validate it using computer-based Monte Carlo simulations as well as real data. Furthermore, we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In the indirect reconstruction, Patlak parametric images are generated by reconstructing a sequence of dynamic PET images first and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In the direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. The PML reconstruction is used in both the indirect and direct reconstruction methods. Simplified analytical expressions for evaluating lesion detectability on Patlak parametric images have been derived and applied to optimize the regularization parameter value for lesion detection. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.

Download or read book Improved PET Image Reconstruction Using Machine Learning Techniques written by and published by . This book was released on 2019 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: In static PET activity imaging and dynamic parametric imaging, maximum a posteriori (MAP) or penalized maximum likelihood reconstruction (ML) algorithms have been proposed to incorporate a regularizer for suppressing the image noise during the reconstruction process. A quadratic regularizer allowing pairwise interaction among neighboring voxels reduces noise at the cost of over smoothing the edges and fine features. Mathematical model based edge preserving regularizers, e.g. the Green roughness (GR) and the total variation (TV) regularizers may not distinguish true edges from noise in practice. We propose to use a superior denoiser, dictionary learning based sparse representation that can efficiently distinguish true features from noise, to regularize the static MAP and dynamic penalized direct reconstructions. The regularization term is formed as the residual of the denoising process, which encourages self-consistency with the denoised version in the updated activity or parametric image. Using simulated and patient static brain PET data, we study the performance of the static DL-MAP algorithm and compare it quantitatively with GR-MAP, patch-based GR-MAP, and TV-MAP algorithms. The proposed DL-MAP algorithm achieves improved bias and contrast at comparable noise compared with the other MAP algorithms. To study the proposed DL direct parametric reconstruction algorithm and evaluate its performance, we stimulate 82Rb dynamic myocardial perfusion (MP) PET data. The advantage of the DL direct algorithm is demonstrated in terms of noise versus bias tradeoff and noise versus contrast tradeoff in the reconstructed K1 images compared with the indirect method with and without post filtering, the direct method without regularization, and the quadratic penalty regularized direct algorithm. Consistent results are achieved when reconstructing patient 82Rb MP PET data. It is worth noting that the dictionary learned from a 3D self-created hollow sphere image yields comparable reconstructed PET images or parametric images to those using the dictionary learned from the corresponding MR images. We demonstrate that the DL-MAP static reconstruction and the DL constrained dynamic direct reconstruction are not restricted to the MR dictionary and have the potential to improve quantitative PET imaging especially when the corresponding MR image is not available. To further improve the performance of general MAP algorithms such that the "unachievable region" defined in the noise/bias plane for a certain MAP is reduced, we propose to develop an artificial neural network (ANN) based MAP reconstruction enhancement scheme. The enhancement is cast as a regression problem that models a nonlinear and spatial varying mapping between the reconstructed image patches and an enhanced image patch. An ANN model named denoising autoencoder (DA) with backpropagation is used to solve this regression through learning from examples. We simulate the brain PET data at different count levels of different subjects with and without lesions. The DA is trained using the image patches reconstructed with a MAP algorithm of different regularization parameters for one normal subject at a certain count level. The performance of the trained DA is evaluated to process reconstructed images from other simulations and two patient brain PET imaging datasets. In every testing case, we demonstrate that the DA enhancement technique improves the noise and bias tradeoff compared with the MAP reconstruction using different regularizing weights thus decreasing the size of the unachievalbe region in the noise/bias plane. In addition to the development of the DL penalized direct parametric reconstruction for dynamic PET imaging, we propose to use the DA denoising approach to improve the indirect parametric reconstruction in dynamic SV2A PET imaging with reduced dose of 11C-UCB-J. Due to high brain uptake, injecting standard-dose of 11C-UCB-J results in high quality dynamic frames. Using the DA denoising technique, we explore the possibility of a substantially reduced radioactivity does to produce comparable dynamic frames. The DA network is trained to form a nonlinear mapping from image patches in the reduced-dose dynamic frames to the corresponding patches in the standard-dose dynamic frames of one healthy control (HC) subject. The trained DA model is then applied to denoise the reduced-dose dynamic frames of other two HCs and two Alzheimer's disease (AD) patients. Voxel-wise kinetic analysis is performed to generate parametric images from the dynamic frames pre and post DA denoising. The proposed DA denoising method suppresses noise without introducing bias in the dynamic frames as well as the parametric images. Achieving noise reductions of approximately 40% in the dynamic frames of different HCs and AD patients, the DA denoising method demonstrates the potential of equivalently increasing the injection dose by 3 fold for the dynamic SV2A PET imaging. Overall, the developed machine learning techniques as verified to static and dynamic MAP reconstructions are promising for improving quantitative PET imaging.

Download or read book Statistical Image Reconstruction Algorithms Using Paraboloidal Surrogates for PET Transmission Scans written by Hakan Erdoğan and published by . This book was released on 1999 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Radiology Nuclear Medicine Diagnostic Imaging written by Ali Gholamrezanezhad and published by John Wiley & Sons. This book was released on 2023-07-03 with total page 916 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radiology-Nuclear Medicine Diagnostic Imaging “p>Radiology-Nuclear Medicine Diagnostic Imaging: A Correlative Approach provides in-depth guidance on applying the principles of radiologic-nuclear medicine correlation to the interpretation of imaging for diagnostic, prognostic, and predictive indications. Describing the clinical implications of all major imaging modalities, this comprehensive professional reference offers one-stop coverage of the common diagnostic applications encountered by nuclear medicine physicians and radiologists in day-to-day practice. The book develops the nuclear diagnostic skills necessary to interpret combined imaging modalities and correlate radiologic findings using a disease and organ-based approach to radiologic interpretation. Thematically organized sections explore a variety of pathologies including diseases of the head and neck, gastrointestinal tract, and pulmonary, endocrine, and central nervous system. Written by internationally recognized experts, this important resource: Helps physicians better understand the clinical and treatment implications of diseases with characteristic radiologic appearances Includes detailed descriptions of nuclear medicine presentations of diseases of most organ systems combined with radiologic correlation Explains refinement of differential diagnoses in various organ systems based on specific imaging features Demonstrates how to correlate scintigraphy and PET images with radiography, CT, MRI, and other imaging techniques Includes a timely review of the application of nuclear medicine-radiology correlative imaging in research Features practical, hands-on clinical imaging references, and more than 600 color illustrations and high-resolution images throughout Radiology-Nuclear Medicine Diagnostic Imaging: A Correlative Approach is a must-have for both trainee and experienced radiologists, nuclear medicine physicians, and specialist nurses.

Download or read book Emerging Imaging Technologies in Medicine written by Mark A. Anastasio and published by CRC Press. This book was released on 2012-12-06 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the discovery of x-rays in 1895 through the emergence of computed tomography (CT) in the 1970s and magnetic resonance imaging (MRI) in the 1980s, non-invasive imaging has revolutionized the practice of medicine. While these technologies have thoroughly penetrated clinical practice, scientists continue to develop novel approaches that promise to push imaging into entirely new clinical realms, while addressing the issues of dose, sensitivity, or specificity that limit existing imaging approaches. Emerging Imaging Technologies in Medicine surveys a number of emerging technologies that have the promise to find routine clinical use in the near- (less than five years), mid- (five to ten years) and long-term (more than ten years) time frames. Each chapter provides a detailed discussion of the associated physics and technology, and addresses improvements in terms of dose, sensitivity, and specificity, which are limitations of current imaging approaches. In particular, the book focuses on modalities with clinical potential rather than those likely to have an impact mainly in preclinical animal imaging. The last ten years have been a period of fervent creativity and progress in imaging technology, with improvements in computational power, nanofabrication, and laser and detector technology leading to major new developments in phase-contrast imaging, photoacoustic imaging, and optical imaging.

Download or read book Information Processing in Medical Imaging written by Chris Taylor and published by Springer Science & Business Media. This book was released on 2003-07-11 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refeered proceedings of the 18th Interational Conference on Information Processing in Medical Imaging, IPMI 2003, held in UK, in July 2003. The 57 revised full papers presented were carefully reviewed and selected from submissions. The papers are organized in topical sections shape modeling, shape analysis, segmentation, color, performance characterization, registration and modeling similarity, registration and modeling deformation, cardiac motion, fMRI analysis, and diffusion imaging and tractography.

Download or read book Diagnostic Nuclear Medicine written by C. Schiepers and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to present students and professionals with a comprehensive update of recent developments not found in other textbooks on the subject, the various clinical applications of nuclear medicine techniques are considered here, and due attention is also given to radiopharmaceuticals, equipment and instrumentation, reconstruction techniques and the principles of gene imaging

Download or read book Quantification in Nuclear Medicine Imaging written by Ivo Rausch and published by Frontiers Media SA. This book was released on 2022-01-20 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analysis of Signal Detectability in Statistically Reconstructed Tomographic Images written by Anastasia Yendiki and published by . This book was released on 2005 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Information Processing in Medical Imaging written by Jerry L. Prince and published by Springer. This book was released on 2009-07-30 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refeered proceedings of the 21st International Conference on Information Processing in Medical Imaging, IPMI 2009, held in Williamsburg, VA, USA, in July 2009 The 26 revised full papers and 33 revised poster papers presented were carefully reviewed and selected from 150 submissions. The papers are organized in topical sections on diffusion imaging, PET imaging, image registration, functional networks, space curves, tractography, microscopy, exploratory analyses, features and detection, image guided surgery, shape analysis, motion, and segmentation and validation.

Download or read book Neuroimaging Techniques in Clinical Practice written by Manoj Mannil and published by Springer Nature. This book was released on 2020-08-11 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a concise overview of emerging technologies in the field of modern neuroimaging. Fundamental principles of the main imaging modalities are described as well as advanced imaging techniqes including diffusion weighted imaging, perfusion imaging, arterial spin labeling, diffusion tensor imaging, intravoxel incoherent motion, MR spectroscopy, functional MRI, and artificial intelligence. The physical concepts underlying each imaging technique are carefully and clearly explained in a way suited to a medical audience without prior technical knowledge. In addition, the clinical applications of the various techniques are described with the aid of illustrative clinical examples. Helpful background information is also presented on the core principles of MRI and the evolution of neuroimaging, and important references to current medical research are highlighted. The book will meet the needs of a range of non-technological professionals with an interest in advanced neuroimaging, including radiology researchers and clinicians in the fields of neurology, neurosurgery, and psychiatry.

Download or read book Image Reconstruction from Projections written by Gabor T. Herman and published by . This book was released on 1980 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image reconstruction from projections. Probability and random variables. An overview of the process of CT. Physical problems associated with data collection in CT. Computer simulation of data collection in CT. Data collection and reconstruction of the head phantom under various assumptions. Basic concepts of reconstruction algorithms. Backprojection. Convolution method for parallel beams. Other transform methods for parallel beams. Convolution methods for divergent beams. The algebraic reconstruction techniques. Quadratic optimization methods. Noniterative series expansion methods. Truly three-dimensional reconstruction. Three-dimensional display of organs. Mathematical background.

Download or read book Image Models and their Speech Model Cousins written by Stephen Levinson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IMA Volume in Mathematics and its Applications IMAGE MODELS (AND THEIR SPEECH MODEL COUSINS) is based on the proceedings of a workshop that was an integral part of the 1993-94 IMA program on "Emerging Applications of Probability." We thank Stephen E. Levinson and Larry Shepp for organizing the workshop and for editing the proceedings. We also take this opportunity to thank the National Science Foundation, the Army Research Office, and the National Security Agency, whose financial support made the workshop possible. A vner Friedman Willard Miller, Jr. v PREFACE This volume is an attempt to explore the interface between two diverse areas of applied mathematics that are both "customers" of the maximum likelihood methodology: emission tomography (on the one hand) and hid den Markov models as an approach to speech understanding (on the other hand). There are other areas where maximum likelihood is used, some of which are represented in this volume: parsing of text (Jelinek), microstruc ture of materials (Ji), and DNA sequencing (Nelson). Most of the partici pants were in the main areas of speech or emission density reconstruction. Of course, there are many other areas where maximum likelihood is used that are not represented here.

Download or read book PET CT in Lung Cancer written by Archi Agrawal and published by Springer. This book was released on 2018-02-16 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, excellently illustrated pocket book provides an up-to-date summary of the science and practice of PET/CT imaging in lung cancer. The coverage encompasses the entire spectrum of lung cancer – pathology, radiological and PET/CT imaging, and management. Readers will also find information on the physics of PET and its use in respiratory gating and radiotherapy planning. The highlights of the book are the exquisite depiction of normal variants, pitfalls, and artifacts and a pictorial atlas of the various types of lung cancer and their manifestations. The contributing authors are well-known and experienced oncologists, pathologists, radiologists, and nuclear physicians. This book has been compiled under the auspices of the British Nuclear Medicine Society. It will be of high value for nuclear physicians, radiologists, referring clinicians and oncologists, and paramedical staff working in these fields

Download or read book 2004 IEEE Nuclear Science Symposium Conference Record written by and published by . This book was released on 2004 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Tomosynthesis Imaging written by Ingrid Reiser and published by Taylor & Francis. This book was released on 2014-03-12 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: An innovative, three-dimensional x-ray imaging technique that enhances projection radiography by adding depth resolution, Tomosynthesis Imaging explores tomosynthesis, an emerging limited-angle tomographic imaging technology that is being considered for use in a range of clinical applications, and is currently being used for breast cancer screening and diagnosis. While conventional mammography has been very successful in reducing breast cancer mortality, it is not perfect. A major limitation of mammography is that the recorded image represents the superposition of complex three-dimensional structures in the breast onto a two-dimensional plane, making detection and diagnosis of breast cancer challenging. Tomosynthesis produces quasi-three-dimensional images that can significantly enhance the visualization of important diagnostic features. This book highlights the flexibility of tomosynthesis systems for new clinical applications, and provides a detailed discussion of the tomosynthesis acquisition process and the impact of physical factors. It explores such topics as acquisition parameters, system components, modeling, image reconstruction algorithms, and system evaluation. Provides in-depth coverage of system design considerations, as well as image reconstruction strategies Describes the current state of clinical applications of tomosynthesis, including imaging of the breast and chest, as well as its use in radiotherapy Illustrates the merits of tomosynthesis imaging and its potential clinical applications in imaging of the breast and chest, as well as for radiation therapy Divided into five sections, this text delves into the history and development of tomosynthesis. It introduces tomosynthesis imaging, discusses imaging system design considerations, and reviews image reconstruction algorithms that have been developed for tomosynthesis. It also describes system evaluation methodologies, emphasizes current clinical applications, and examines the future direction for tomosynthesis.

Download or read book Medical Imaging Systems written by Andreas Maier and published by Springer. This book was released on 2018-08-02 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are closely related to traditional camera systems such as endoscopy and microscopy. This is followed by more complex image formation processes: magnetic resonance imaging, X-ray projection imaging, computed tomography, X-ray phase-contrast imaging, nuclear imaging, ultrasound, and optical coherence tomography.