Download or read book An Effective Technique for Multi modal Image Registration written by Md Tanvir Hossain and published by . This book was released on 2012 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image registration brings two images into alignment despite any initial misalignment. Multi-modal image registration is a special type of registration problem where complexity is added, due to images being captured by different types of imaging devices. For decades, researchers have continued to work on multi-modal image registration. Yet limited attention has been paid to developing local feature descriptors for multi-modal registration, despite their useful performance in general registration problems. We would argue that multi-modal registration can therefore benefit from qualities that are inherent in local techniques.In this thesis, we focus on developing a new multi-modal image registration technique based on local descriptors. We study a range of local feature description techniques, acquire an in-depth understanding of relevant sub-procedures and propose a novel modality invariant feature description technique that can be effectively applied to multi-modal image registration. The proposed technique has four components which are carefully designed to cater for variations in image properties caused by multi-modality as well as to enable finding correspondences with high accuracy under a wide range of transformations.We identify certain properties of multi-modal images, namely gradient and region reversal, which must be addressed appropriately in order to register multi-modal images. The first component of our proposed technique overcomes problems with existing local multi-modal techniques in addressing these properties. The second component comprises strategies to encode gradient profiles that are appropriate for multi-modal registration applications. The third component employs a robust and powerful data fitting technique, namely Hough Transform, in order to achieve high accuracy in multi-modal registration. Our proposed solution is simple, but effective, and enables seamless integration of Hough Transform by overcoming existing technical limitations. The final component incorporates special methodologies to cater for local rotations in input images. Besides evaluating our technique in terms of the accuracy of identified correspondences, we also show that the proposed technique results in less registration error when compared with existing techniques.
Download or read book Robust and Effective Techniques for Multi modal Image Registration written by Guohua Lv and published by . This book was released on 2015 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image registration is the process of estimating the optimal transformation that aligns different imaging data into spatial correspondences. Multi-modal image registration is to register images which are captured by different types of imaging devices. This thesis aims to develop robust and effective techniques for multi-modal image registration. The challenge lies in the fact that the visual appearance may differ a lot between corresponding parts of multi-modal images. We have been exploring ways by investigating local image features.Two main contributions have been made in this thesis.First, we have improved existing mono-modal and multi-modal image registration techniques by better utilizing gradient information. For a feature-based image registration technique, its effectiveness to a large extent relies on the discrimination power of local descriptors. In the existing techniques, gradient information is utilized in a number of ways for building local descriptors. We have analyzed the limitations of these techniques, and have proposed a technique for better utilizing gradient information. As a result, the discrimination power of local descriptors has been enhanced, leading to a better registration performance.Second, we have developed a new multi-modal image registration technique, which has the following innovations:1. We have proposed a technique to detect the intrinsic structural similarity in multi-modal microscopic images. This is achieved by exploiting the characteristics in intensity relationships between the Red-Green-Blue color channels.2. To increase robustness to content differences, contour-based corners are used, instead of intensity-based keypoints in a state-of-the-art multi-modal image registration technique.3. We have proposed a new local descriptor to better represent corners.4. We have proposed a new way of scale estimation by making use of geometric relationships between corner triplets in two images.The proposed multi-modal image registration technique achieves greater robustness in terms of both content differences and scale differences as compared to the state-of-the-art multi-modal image registration technique.
Download or read book Multi modal Image Registration with Unsupervised Deep Learning written by Courtney K. Guo and published by . This book was released on 2019 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we tackle learning-based multi-modal image registration. Multi-modal registration, in which two images of dierent modalities need to be aligned to each other, is a difficult yet essential task for medical imaging analysis. Classical methods have been developed for single-modal and multi-modal registration, but are slow because they solve an optimization problem for each pair of images. Recently, deep learning methods for registration have been proposed, and have been shown to shorten registration time by learning a global function to perform registration, which can then be applied quickly on a pair of test images. These methods perform well for single-modal registration but have not yet been extended to the harder task of multi-modal registration. We bridge this gap by implementing classical multi-modal metrics in a differentiable and efficient manner to enable deep image registration for multi-modal data. We nd that our method for multi-modal registration performs significantly better than baselines, in terms of both accuracy and runtime.
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 Instrumentation an Issue of Pet Clinics written by Habib Zaidi and published by Saunders. This book was released on 2008-03 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Currently there is no shortage of challenges and opportunities for PET instrumentation and quantitative imaging techniques. Molecular imaging technologies are leading to a revolutionary paradigm shift in health care and clinical practice. This issue reviews recent advances in PET instrumentation as well as volume correction strategies and strategies for motion tracking and correction, scatter compensation techniques, and attenuation correction techniques.
Download or read book Image Registration for Remote Sensing written by Jacqueline Le Moigne and published by Cambridge University Press. This book was released on 2011-03-24 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a summary of current research in the application of image registration to satellite imagery. Presenting algorithms for creating mosaics and tracking changes on the planet's surface over time, it is an indispensable resource for researchers and advanced students in Earth and space science, and image processing.
Download or read book Efficient Multi modal Image Registration Based on Gradient Orientations of Minimal Uncertainty written by Dante De Nigris Moreno and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This thesis presents a general framework for the registration of medicalimages across multiple clinical contexts involving rigid and non-rigidapplications. The proposed framework relies on gradient orientations asprimitive geometric descriptors so as to locally assess image similarity basedon orientation alignment and evaluates the metric on sparse locationscorresponding to anatomical boundaries of interest. The two main advantagesbrought forward by the proposed approach are: (1) a substantial reduction incomputational complexity and processing time and (2) a significant improvementin robustness against multi-modal contexts with widely different imageformation models and significant non-homogeneities.The proposed approach is evaluated in multiple clinical contexts and comparedagainst state-of-the-art techniques. In the context of neurosurgery, imageregistration can be employed so as to update a pre-operative magneticresonance image (MRI) based on an intra-operative ultrasound volume. Theproposed approach is evaluated in this challenging time-sensitive scenario andis shown to provide robust performance with sub-second processing times. Inthe context of the rigid registration of computational tomography (CT) and MRIbrain volumes, the proposed approach is evaluated with a publicly availabledataset and compared against previously proposed techniques. The quantitativeresults demonstrate that the proposed approach can employ highly reducedsampling rates (e.g. only 0.05% of the voxels in the image) while stillyielding a median registration error inferior to 1mm. In the context of thenon-rigid registration of inter-patient MRI brain volumes, the proposedapproach is evaluated with a publicly available dataset which measuresregistration accuracy in terms of the agreement of spatially mapped labelswith expert annotated labels. The use of such dataset allows for a fair andunbiased comparison with over fourteen competing techniques. The quantitativeresults show that the proposed approach achieves slightly inferior accuracythan the top performing method but with only one sixth of the processing timerequired by the alternative technique. Finally, the proposed approach isevaluated in the context of automatic brain lesion detection which relies onhealthy tissue probability maps obtained via registration to a brain atlas.The quantitative comparison against two leading image registration techniquesshows that the proposed approach can lead to a slightly improved performanceof brain lesion detection algorithms while requiring only one sixth of theprocessing time used by competing registration approaches." --
Download or read book Medical Image Processing written by Satya Prakash Yadav and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-09-23 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis.
Download or read book Mathematical Methods in Image Processing and Inverse Problems written by Xue-Cheng Tai and published by Springer Nature. This book was released on 2021-09-25 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains eleven original and survey scientific research articles arose from presentations given by invited speakers at International Workshop on Image Processing and Inverse Problems, held in Beijing Computational Science Research Center, Beijing, China, April 21–24, 2018. The book was dedicated to Professor Raymond Chan on the occasion of his 60th birthday. The contents of the book cover topics including image reconstruction, image segmentation, image registration, inverse problems and so on. Deep learning, PDE, statistical theory based research methods and techniques were discussed. The state-of-the-art developments on mathematical analysis, advanced modeling, efficient algorithm and applications were presented. The collected papers in this book also give new research trends in deep learning and optimization for imaging science. It should be a good reference for researchers working on related problems, as well as for researchers working on computer vision and visualization, inverse problems, image processing and medical imaging.
Download or read book Biomedical Image Registration written by James C. Gee and published by Springer Science & Business Media. This book was released on 2003-10-13 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2nd International Workshop on Biomedical Image Registration (WBIR) was held June 23–24, 2003, at the University of Pennsylvania, Philadelphia. Following the success of the ?rst workshop in Bled, Slovenia, this meeting aimed to once again bring together leading researchers in the area of biomedical image registration to present and discuss recent developments in the ?eld. Thetheory,implementationandapplicationofimageregistrationinmedicine have become major themes in nearly every scienti?c forum dedicated to image processingandanalysis. Thisintenseinterestre?ectsthe?eld’simportantrolein theconductofabroadandcontinuallygrowingrangeofstudies. Indeed,thete- niques have enabled some of the most exciting contemporary developments in the clinical and research application of medical imaging, including fusion of m- timodality data to assist clinical interpretation; change detection in longitudinal studies; brain shift modeling to improve anatomic localization in neurosurgical procedures; cardiac motion quanti?cation; construction of probabilistic atlases of organ structure and function; and large-scale phenotyping in animal models. WBIR was conceived to provide the burgeoning community of investigators in biomedical image registration an opportunity to share, discuss and stimulate developments in registration research and application at a meeting exclusively devoted to the topic. The format of this year’s workshop consisted of invited talks, author presentations and ample opportunities for discussion, the latter including an elegant reception and dinner hosted at the Mutter ̈ Museum. A representation of the best work in the ?eld, selected by peer review from full manuscripts,waspresentedinsingle-tracksessions. Thepapers,whichaddressed the full diversity of registration topics, are reproduced in this volume, along with enlightening essays by some of the invited speakers.
Download or read book Patch Based Techniques in Medical Imaging written by Guorong Wu and published by Springer. This book was released on 2016-01-07 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Patch-based Techniques in Medical Images, Patch-MI 2015, which was held in conjunction with MICCAI 2015, in Munich, Germany, in October 2015. The 25 full papers presented in this volume were carefully reviewed and selected from 35 submissions. The topics covered are such as image segmentation of anatomical structures or lesions; image enhancement; computer-aided prognostic and diagnostic; multi-modality fusion; mono and multi modal image synthesis; image retrieval; dynamic, functional physiologic and anatomic imaging; super-pixel/voxel in medical image analysis; sparse dictionary learning and sparse coding; analysis of 2D, 2D+t, 3D, 3D+t, 4D, and 4D+t data.
Download or read book Multi Modality State of the Art Medical Image Segmentation and Registration Methodologies written by Ayman S. El-Baz and published by Springer Science & Business Media. This book was released on 2011-05-04 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advances in image guided surgery for cancer treatment, the role of image segmentation and registration has become very critical. The central engine of any image guided surgery product is its ability to quantify the organ or segment the organ whether it is a magnetic resonance imaging (MRI) and computed tomography (CT), X-ray, PET, SPECT, Ultrasound, and Molecular imaging modality. Sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures present in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning system designs. The focus of this book in towards the state of the art techniques in the area of image segmentation and registration.
Download or read book A New Method for Multimodal 3 D Image Registration Using External Markers written by Antoine B. Abche and published by . This book was released on 1996 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support written by Kenji Suzuki and published by Springer Nature. This book was released on 2019-10-24 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning.
Download or read book Multimodal Brain Image Analysis written by Tianming Liu and published by Springer Science & Business Media. This book was released on 2011-09-15 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Multimodal Brain Image Analysis, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 15 revised full papers presented together with 4 poster papers were carefully reviewed and selected from 24 submissions. The objective of this workshop is to facilitate advancements in the multimodal brain image analysis field, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications.
Download or read book Feature selection for multi modal image registration using mutual information written by Víctor Rodríguez Gil and published by . This book was released on 2002 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applied Video Processing in Surveillance and Monitoring Systems written by Dey, Nilanjan and published by IGI Global. This book was released on 2016-10-11 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Video monitoring has become a vital aspect within the global society as it helps prevent crime, promote safety, and track daily activities such as traffic. As technology in the area continues to improve, it is necessary to evaluate how video is being processed to improve the quality of images. Applied Video Processing in Surveillance and Monitoring Systems investigates emergent techniques in video and image processing by evaluating such topics as segmentation, noise elimination, encryption, and classification. Featuring real-time applications, empirical research, and vital frameworks within the field, this publication is a critical reference source for researchers, professionals, engineers, academicians, advanced-level students, and technology developers.
