Semantic Assisted, Multiresolution Image Retrieval in 3D Brain MR Volumes

Content Based Image Retrieval (CBIR) is an important research area in the field of multimedia information retrieval. The application of CBIR in the medical domain has been attempted before, however the use of CBIR in medical diagnostics is a daunting task. The goal of diagnostic medical image retrieval is to provide diagnostic support by displaying relevant past cases, along with proven pathologies as ground truths. Moreover, medical image retrieval can be extremely useful as a training tool for medical students and residents, follow-up studies, and for research purposes. Despite the presence of an impressive amount of research in the area of CBIR, its acceptance for mainstream and practical applications is quite limited. The research in CBIR has mostly been conducted as an academic pursuit, rather than for providing the solution to a need. For example, many researchers proposed CBIR systems where the image database consists of images belonging to a heterogeneous mixture of man-made objects and natural scenes while ignoring the practical uses of such systems. Furthermore, the intended use of CBIR systems is important in addressing the problem of "Semantic Gap". Indeed, the requirements for the semantics in an image retrieval system for pathological applications are quite different from those intended for training and education. Moreover, many researchers have underestimated the level of accuracy required for a useful and practical image retrieval system. The human eye is extremely dexterous and efficient in visual information processing; consequently, CBIR systems should be highly precise in image retrieval so as to be useful to human users. Unsurprisingly, due to these and other reasons, most of the proposed systems have not found useful real world applications. In this dissertation, an attempt is made to address the challenging problem of developing a retrieval system for medical diagnostics applications. More specifically, a system for semantic retrieval of Magnetic Resonance (MR) images in 3D brain volumes is proposed. The proposed retrieval system has a potential to be useful for clinical experts where the human eye may fail. Previously proposed systems used imprecise segmentation and feature extraction techniques, which are not suitable for precise matching requirements of the image retrieval in this application domain. This dissertation uses multiscale representation for image retrieval, which is robust against noise and MR inhomogeneity. In order to achieve a higher degree of accuracy in the presence of misalignments, an image registration based retrieval framework is developed. Additionally, to speed-up the retrieval system, a fast discrete wavelet based feature space is proposed. Further improvement in speed is achieved by semantically classifying of the human brain into various "Semantic Regions", using an SVM based machine learning approach. A novel and fast identification system is proposed for identifying a 3D volume given a 2D image slice. To this end, we used SVM output probabilities for ranking and identification of patient volumes. The proposed retrieval systems are tested not only for noise conditions but also for healthy and abnormal cases, resulting in promising retrieval performance with respect to multi-modality, accuracy, speed and robustness. This dissertation furnishes medical practitioners with a valuable set of tools for semantic retrieval of 2D images, where the human eye may fail. Specifically, the proposed retrieval algorithms provide medical practitioners with the ability to retrieve 2D MR brain images accurately and monitor the disease progression in various lobes of the human brain, with the capability to monitor the disease progression in multiple patients simultaneously. Additionally, the proposed semantic classification scheme can be extremely useful for semantic based categorization, clustering and annotation of images in MR brain databases. This research framework may evolve in a natural progression towards developing more powerful and robust retrieval systems. It also provides a foundation to researchers in semantic based retrieval systems on how to expand existing toolsets for solving retrieval problems

ULTRA CLOSE-RANGE DIGITAL PHOTOGRAMMETRY AS A TOOL TO PRESERVE, STUDY, AND SHARE SKELETAL REMAINS

Skeletal collections around the world hold valuable and intriguing knowledge about humanity. Their potential value could be fully exploited by overcoming current limitations in documenting and sharing them. Virtual anthropology provides effective ways to study and value skeletal collections using three-dimensional (3D) data, e.g. allowing powerful comparative and evolutionary studies, along with specimen preservation and dissemination. CT- and laser scanning are the most used techniques for three-dimensional reconstruction. However, they are resource-intensive and, therefore, difficult to be applied to large samples or skeletal collections. Ultra close-range digital photogrammetry (UCR-DP) enables photorealistic 3D reconstructions from simple photographs of the specimen. However, it is the least used method in skeletal anthropology and the lack of appropriate protocols often limit the quality of its outcomes. This Ph.D. thesis explored UCR-DP application in skeletal anthropology. The state-of-the-art of this technique was studied, and a new approach based on cloud computing was proposed and validated against current gold standards. This approach relies on the processing capabilities of remote servers and a free-for-academic use software environment; it proved to produce measurements equivalent to those of osteometry and, in many cases, they were more precise than those of CT-scanning. Cloud-based UCR-DP allowed the processing of multiple 3D models at once, leading to a low-cost, quick, and effective 3D production. The technique was successfully used to digitally preserve an initial sample of 534 crania from the skeletal collections of the Museo Sardo di Antropologia ed Etnografia (MuSAE, Università degli Studi di Cagliari). Best practices in using the technique for skeletal collection dissemination were studied and several applications were developed including MuSAE online virtual tours, virtual physical anthropology labs and distance learning, durable online dissemination, and values-led participatorily designed interactive and immersive exhibitions at the MuSAE. The sample will be used in a future population study of Sardinian skeletal characteristics from the Neolithic to modern times. In conclusion, cloud-based UCR-DP offers many significant advantages over other 3D scanning techniques: greater versatility in terms of application range and technical implementation, scalability, photorealistic restitution, reduced requirements relating to hardware, labour, time, and cost, and is, therefore, the best choice to document and value effectively large skeletal samples and collections

Book of short Abstracts of the 11th International Symposium on Digital Earth

The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium

Earth resources: A continuing bibliography with indexes (issue 51)

This bibliography lists 382 reports, articles and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1986. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Aerospace medicine and biology: A cumulative index to a continuing bibliography (supplement 371)

This publication is a cumulative index to the abstracts contained in Supplements 359 through 370 of Aerospace Medicine and Biology: A Continuing Bibliography. It includes seven indexes: subject, personal author, corporate source, foreign technology, contract number, report number, and accession number

Annual Report of the University, 2000-2001, Volumes 1-4

Message from the President Thank you for joining me in this look back over the past year at the University of New Mexico. It was a year filled with activity, accomplishment and challenge, and this is our opportunity to reflect back on that year. In 2000-2001 we engaged in a University-wide strategic planning process that called on the energies and talents of hundreds of individuals- faculty, staff, students and members of our broader community. The plan, which will be completed in Fall 2001, will serve as our roadmap for the future and will guide our efforts to capitalize on the opportunities and to meet the challenges of the next several years. This process has encouraged us to examine closely our mission and our values, who we are and what we aspire to become. It has given us reason to be proud of our past and cause to think seriously about how we must change in the future. While this was a year for looking ahead, it was also a year of significant accomplishment. For example, we launched a comprehensive set of programs designed to enrich the academic and social experiences of our undergraduate students. We began the implementation of Freshman Learning Communities where small cohorts of students study and learn together in a common set of courses under the guidance of a senior faculty scholar. We reorganized our advisement systems, we undertook the construction or renovation of student-centered facilities on campus, and we created new support systems to enhance student academic success. It was a year in which our support of faculty, staff and students was our highest priority. Through the support of the New Mexico Legislature, faculty and staff received significant salary increases. A new health benefits plan for graduate assistants was implemented. Our Staff as Students program enabled more than 40 staff members to obtain UNM degrees. And, a Center for Scholarship in Teaching and Learning was established to assist faculty in their efforts to develop more effective teaching skills. Finally, this was a year in which UNM dramatically expanded its role in the local community and throughout the state. Never before has the University been as active or as visible in meeting its public responsibility as it was in 2000-2001. From its active participation in economic development initiatives, to its involvement in K-12 educational improvement efforts, to its significant leadership role in health care delivery, UNM demonstrated its ability to help the state meet its most pressing social challenges. And, as UNM took on a more visible role in supporting the state\\u27s citizens, the support for UNM was returned in kind. This year, annual giving to the University rose to a record 35.3 million dollars, a 40% increase over just two years ago. All told, it has been a gratifying and successful year. However, we cannot allow our past accomplishments to mask the continued challenges facing this University. Neither will we allow these challenges to dominate our thinking and diminish out pride in what the University has achieved. So we will savor our successes and continue to move forward. As always, we thank you for sharing our dreams and for supporting the University of New Mexico. Sincerely, William C. Gordon, Presiden

Concepts and Approaches for Mars Exploration

Abstracts describe missions, mission elements or experiments for consideration in the 2005-2020 time frame. Also the technologies and the support necessary to achieve the results are discussed.NASA Headquarters; Lunar and Planetary Institutehosted by Lunar and Planetary Institute ; sponsored by NASA Headquarters, Lunar and Planetary Institute ; convener Scott Hubbard

Automatic building of a visual interface for content-based multiresolution retrieval of paleontology images

International audienc