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Vision loss, with a prevalence loss greater than 42 million in the United States is one of the major challenges of today's health-care industry and medical science. Early detection of different retinal-related diseases will dramatically reduce the risk of vision loss. Optical Coherence Tomography (OCT) is a relatively new imaging technique which is of great importance in the identification of ocular and especially retinal diseases. Thus, the efficient analysis of OCT images provides several advantages. In this thesis, we propose a series of image processing and machine learning techniques for the automated analysis of OCT images. The proposed methodology in chapter 2 localizes different retinal layers using a modified version of active contour models. In chapter 3, we propose a method which classifies OCT images based on different pathological conditions using novel methods, e.g., transfer learning and new texture detection techniques. The proposed methods along with the clinically meaningful extracted characteristics provide numbers of applications and benefits, e.g., saving a considerable amount of time and providing more-efficient and -accurate indices for the diagnosis and treatment of different ocular diseases to ophthalmologists and finally reducing the overall risk of vision loss.
This book introduces the latest optical coherence tomography (OCT) imaging and computerized automatic image analysis techniques, and their applications in the diagnosis and treatment of retinal diseases. Discussing the basic principles and the clinical applications of OCT imaging, OCT image preprocessing, as well as the automatic detection and quantitative analysis of retinal anatomy and pathology, it includes a wealth of clinical OCT images, and state-of-the-art research that applies novel image processing, pattern recognition and machine learning methods to real clinical data. It is a valuable resource for researchers in both medical image processing and ophthalmic imaging.
This book covers the results of the creation of methods for ophthalmologists support in OCT images automated analysis. These methods, like the application developed on their basis, are used during routine examinations carried out in hospital. The monograph comprises proposals of new and also of known algorithms, modified by authors, for image analysis and processing, presented on the basis of example of Matlab environment with Image Processing tools. The results are not only obtained fully automatically, but also repeatable, providing doctors with quantitative information on the degree of pathology occurring in the patient. In this case the anterior and posterior eye segment is analysed, e.g. the measurement of the filtration angle or individual layers thickness. To introduce the Readers to subtleties related to the implementation of selected fragments of algorithms, the notation of some of them in the Matlab environment has been given. The presented source code is shown only in the form of example of implementable selected algorithm. In no way we impose here the method of resolution on the Reader and we only provide the confirmation of a possibility of its practical implementation.
Aim. Optical Coherence Tomography (OCT) is a fast and non-invasive medical imaging technique which helps in the investigation of each individual retinal layer structure. For early detection of retinal diseases and the study of their progression, segmentation of the OCT images into the distinct layers of the retina plays a crucial role. However, segmentation done by the clinicians manually is extremely tedious, time-consuming and variable with respect to the expertise level. Hence, there is an utmost necessity to develop an automated segmentation algorithm for retinal OCT images which is fast, accurate, and eases clinical decision making. Methods. Graph-theoretical methods have been implemented to develop an automated segmentation algorithm for spectral domain OCT (SD-OCT) images of the retina. As a pre-processing step, the best method for denoising the SD-OCT images prior to graph-based segmentation was determined by comparison between simple Gaussian filtering and an advanced wavelet-based denoising technique. A shortest-path based graph search technique was implemented to accurately delineate intra-retinal layer boundaries within the SD-OCT images. The results from the automated algorithm were also validated by comparison with manual segmentation done by an expert clinician using a specially designed graphical user interface (GUI). Results. The algorithm delineated seven intra-retinal boundaries thereby segmenting six layers of the retina along with computing their thicknesses. The thickness results from the automated algorithm when compared to normative layer thickness values from a published study showed no significant differences (p > 0.05) for all layers except layer 4 (p = 0.04). Furthermore, when a comparative analysis was done between the results from the automated segmentation algorithm and that from manual segmentation by an expert, the accuracy of the algorithm varied between 74.58% (layer 2) to 98.90% (layer 5). Additionally, the comparison of two different denoising techniques revealed that there was no significant impact of an advanced wavelet-based denoising technique over the use of simple Gaussian filtering on the accuracy of boundary detection by the graph-based algorithm. Conclusion. An automated graph-based algorithm was developed and implemented in this thesis for the segmentation of seven intra-retinal boundaries and six layers in SD-OCT images which is as good as manual segmentation by an expert clinician. This thesis also concludes on the note that simple Gaussian filters are sufficient to denoise the images in graph-based segmentation techniques and does not require an advanced denoising technique. This makes the complexity of implementation far more simple and efficient in terms of time and memory requirements.
Optical coherence tomography angiography (OCTA) has undergone tremendous growth since its first commercial introduction in 2014. Because it provides injection-free, capillary-resolution, 3-dimensional angiography of the retina and choroid, OCTA is likely to overtake fluorescein as the most important angiographic imaging technique in the eye. Nearly all manufacturers of ophthalmic OCT now offer OCTA products. A PubMed search now yields over 5700 articles on OCTA and related terms. Clinical investigators have already found a use for OCTA in almost every category of retinal and optic nerve diseases. This book is meant to bring together all this information so clinicians can have one authoritative text to turn to as we begin to use this new imaging modality that was never taught when we were in formal training. Table of contents Introduction Dedication About the Editors Contributors 1. Optical coherence tomography systems for angiography 2. Optical coherence tomographic angiography algorithms 3. Vascular anatomy of the normal retina and choroid 4. OCTA of the normal anterior eye circulations 5. Artifacts 6. Quantification 7. Artificial intelligence in optical coherence tomographic angiography 8. Terminology: a new standard 9. AngioVue SSADA OCTA on the Optovue SOLIX Spectral-Domain OCT 10. Optical microangiography with AngioPlex® and PLEX® Elite systems 11. Optical coherence tomography angiography imaging on the Topcon Triton and Maestro2 systems 12. NIDEK Mirante OCT angiography 13. OCTA on the Heidelberg spectralis spectral-domain OCT 14. OCTA on the Optopol REVO NX spectral-domain OCT 15. OCTA on the Canon OCT-HS100 and Xephilio OCT-A1 Spectral-Domain OCT 16. Exudative neovascular age-related macular degeneration—Type 1, 2 and 3 neovascularization 17. Retinal angiomatous proliferation—type 3 choroidal neovascularization 18. Short- and long-term follow-up of macular neovascularization response to antiangiogenic treatment 19. Nonexudative neovascular age-related macular degeneration 20. Non-neovascular age-related macular degeneration 21. Polypoidal choroidal vasculopathy 22. Macular telangiectasia 23. Central serous chorioretinopathy 25. Nonproliferative diabetic retinopathy 26. Subclinical neovascular diabetic retinopathy 27. Proliferative diabetic retinopathy 28. Retinal venous occlusion 29. Retinal arterial occlusion 30. Plexus-specific occlusions in retinal vascular diseases 31. Paracentral acute middle maculopathy 32. Inherited retinal degenerations 33. Pathologic myopia 34. Multimodal imaging and the role of optical coherence tomography angiography in retinal vasculitis 35. White spot syndromes 36. Choroidal tumors 37. Radiation retinopathy 38. Open-angle glaucoma 39. Primary angle-closure glaucoma 40. Optic neuritis and multiple sclerosis 41. Alzheimer’s disease 42. Corneal neovascularization 43. Ocular surface and iris tumors
This open access book provides a comprehensive overview of the application of the newest laser and microscope/ophthalmoscope technology in the field of high resolution imaging in microscopy and ophthalmology. Starting by describing High-Resolution 3D Light Microscopy with STED and RESOLFT, the book goes on to cover retinal and anterior segment imaging and image-guided treatment and also discusses the development of adaptive optics in vision science and ophthalmology. Using an interdisciplinary approach, the reader will learn about the latest developments and most up to date technology in the field and how these translate to a medical setting. High Resolution Imaging in Microscopy and Ophthalmology – New Frontiers in Biomedical Optics has been written by leading experts in the field and offers insights on engineering, biology, and medicine, thus being a valuable addition for scientists, engineers, and clinicians with technical and medical interest who would like to understand the equipment, the applications and the medical/biological background. Lastly, this book is dedicated to the memory of Dr. Gerhard Zinser, co-founder of Heidelberg Engineering GmbH, a scientist, a husband, a brother, a colleague, and a friend.
This book is a printed edition of the Special Issue "Development and Application of Optical Coherence Tomography (OCT)" that was published in Applied Sciences
The second edition of Spectral Domain OCT is a practical guide to the investigation and diagnosis of retinal disease using the Topcon machine. Beginning with an overview of OCT, the book provides a step by step approach to image capture, analysis and interpretation. With the help of numerous case studies, OCT patterns in different types of retinal disease are presented as both 2D and 3D images. In addition, Spectral Domain OCT highlights features of the new Topcon 2000 machine with an enhanced speed of 27,000 A scans/second, improved software algorithms and extra facilities for anterior segment imaging.
Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies
Optical coherence tomography (OCT) angiography is an important new imaging modality that is already being used by ophthalmologists in retina centers worldwide. It uses motion as intrinsic contrast, thus obviating the need to inject any intravenous dye. It uses infrared light that is invisible to the patient, and only requires few seconds per scan. This makes it both easier to use and much better tolerated by patients than traditional dye-based fluorescein angiography (FA) and indocyanine green (ICG) angiography. Inside Optical Coherence Tomography Angiography of the Eye Drs. David Huang, Bruno Lumbroso, Yali Jia, and Nadia Waheed include detailed information on clinical applications and fundamental principles needed to understand and use this new technology. This includes information on high-speed OCT systems, algorithms to extract flow contrast, the appearance of the normal eye, the findings in myriad diseases, and tips on how to deal with artifact and pitfalls. The 3-dimensional nature of OCT angiography provides visualization that was not possible before with either FA or ICG and readers will come to appreciate how this enables the visualization of previously difficult to image vascular beds such as the 4 retinal vascular plexuses (radial peripapillary, superficial, intermediate, and deep), the choriocapillaris, and the deeper choroidal vessels. Given its noninvasive nature and ease of use, OCT angiography imaging is rapidly taking an important place in everyday ophthalmology and may soon replace fluorescein angiography in everyday practice. Optical Coherence Tomography Angiography of the Eye is designed to be the definitive text on this cutting-edge technology for the retina specialist and comprehensive ophthalmologist.