Role of optical storage technology for NASA's image storage and retrieval systems

Author(s):  
Charles D. Benjamin
Author(s):  
Jim Hughes

The receptor head is the system that converts the X-ray beam into a visible image and allows it to be displayed. Modern systems accomplish this by using either an image intensifier (II) or a flat-panel detector (FPD). Both allow real-time fluoroscopy, as well as last-image hold, image storage and retrieval, and other features to assist in procedures or reduce radiation dose. This chapter covers the design and functions of image receptor heads used on C-arm systems that produce images from the incident X-ray beam. This includes the process of intensification and amplification of the image within an II system, as well as the function and the use of newer FPD systems.


Author(s):  
Olugbade Oladokun ◽  
Saul F. C. Zulu

Document description and coding are key operations to information storage and retrieval systems. Description makes it possible for users to obtain information about the documents while coding provides unique numbers to described documents, and enables users to locate, retrieve and store documents manually or electronically. Consequent upon the mass production of information and attendant information explosion, modern libraries and other information dissemination institutions, attached to various institutions, were established. A need therefore arose to put in place systems of achieving bibliographic control over the information produced and collected to facilitate its identification and location wherever it may be found. Among the major systems or tools that information professionals developed to achieve bibliographic control and organization of information include: cataloguing, classification, indexing and abstracting. Using largely documentary sources, the chapter makes a case on the critical role of document description and coding systems in information and knowledge management.


Author(s):  
Görkem Asilioglu ◽  
Emine Merve Kaya ◽  
Duygu Sarikaya ◽  
Shang Gao ◽  
Tansel Ozyer ◽  
...  

Digital image storage and retrieval is gaining more popularity due to the rapidly advancing technology and the large number of vital applications, in addition to flexibility in managing personal collections of images. Traditional approaches employ keyword based indexing which is not very effective. Content based methods are more attractive though challenging and require considerable effort for automated feature extraction. In this chapter, we present a hybrid method for extracting features from images using a combination of already established methods, allowing them to be compared to a given input image as seen in other query-by-example methods. First, the image features are calculated using Edge Orientation Autocorrelograms and Color Correlograms. Then, distances of the images to the original image will be calculated using the L1 distance feature separately for both features. The distance sets will then be merged according to a weight supplied by the user. The reported test results demonstrate the applicability and effectiveness of the proposed approach.


Sign in / Sign up

Export Citation Format

Share Document