Search

The authors have investigated the application of the NASA Advanced Communications Technology Satellite (ACTS) to teleradiology and telemedicine using the Jet Propulsion Laboratory (JPL)-developed ACTS Mobile Terminal (AMT) uplink. In this experiment, bidirectional 128, 256, and 384 kbps satellite links were established between the ACTS/AMT, the ACTS in geosynchronous orbit, and the downlink terrestrial terminal at JPL. A terrestrial Integrated Digital Services Network (ISDN) link was established from JPL to the University of Washington Department of Radiology to complete the bidirectional connection. Ultrasound video imagery was compressed in real-time using video codecs adhering to the International Telecommunication Union-Telecommunication Standardization Sector (ITU-T) Recommendation H.261. A 16 kbps in-band audio channel was used throughout. A five-point Likert scale was used to evaluate the quality of the compressed ultrasound imagery at the three transmission bandwidths (128, 256, and 384 kbps). The central question involved determination of the bandwidth requirements to provide sufficient spatial and contrast resolution for the remote visualization of fine- and low-contrast objects. The 384 kbps bandwidth resulted in only slight tiling artifact and fuzziness owing to the quantizer step size; however, these motion artifacts were rapidly resolved in time at this bandwidth. These experiments have demonstrated that real-time compressed ultrasound video imagery can be transmitted over multiple ISDN line bandwidth links with sufficient temporal, contrast, and spatial resolution for clinical diagnosis of multiple disease and pathology states to provide subspecialty consultation and educational at a distance. Copyright (c) 1999 by W.B. Saunders Company [ABSTRACT FROM AUTHOR]

There is continual pressure on the radiology department to increase its productivity. Two important links to productivity in the computed/digital radiography (CR/DR) workflow chain are the postprocessing step by technologists and the primary diagnosis step by radiologists, who may apply additional image enhancements to aid them in diagnosis. With the large matrix size of CR and DR images and the computational complexity of these algorithms, it has been challenging to provide interactive image enhancement, particularly on full-resolution images. We have used a new programmable processor as the main computing engine of enhancement algorithms for CR or DR images. We have mapped these algorithms to the processor, maximally utilizing its architecture. On a 12-bit 2688 x 2688 image, we have achieved the execution time of 465A ms for adaptive unsharp masking, window/level, image rotate, and lookup table operations using a single processor, which represents at least an order of magnitude improvement compared to the response time of current systems. This kind of performance facilitates rapid computation with preset parameter values and/or enables truly interactive QA processing on radiographs by technologists. The fast response time of these algorithms would be especially useful in a real-time radiology setting, where the radiologist's waiting time in performing image enhancements before making diagnosis can be greatly reduced. We believe that the use of these processors for fast CR/DR image computing coupled with the seamless flow of images and patient data will enable the radiology department to achieve higher productivity.

Over the last decade, a picture archiving and communications system (PACS) has been accepted by an increasing number of clinical organizations. Today, PACS is considered as an essential image management and productivity enhancement tool. Image compression could further increase the attractiveness of PACS by reducing the time and cost in image transmission and storage as long as 1) image quality is not degraded and 2) compression and decompression can be done fast and inexpensively. Compared to JPEG, JPEG 2000 is a new image compression standard that has been designed to provide improved image quality at the expense of increased computation. Typically, the decompression time has a direct impact on the overall response time taken to display images after they are requested by the radiologist or referring clinician. In this paper, we present a fast JPEG 2000 decoder running on a low-cost programmable processor. It can decode a losslessly compressed 2048 x 2048 CR image in 1.51 s. Using this kind of a decoder, performing JPEG 2000 decompression at the PACS display workstation right before images are displayed becomes viable. A response time of 2 s can be met with an effective transmission throughput between the central short-term archive and the workstation of 4.48 Mb/s in case of CT studies and 20.2 Mb/s for CR studies. We have found that JPEG 2000 decompression at the workstation is advantageous in that the desired response time can be obtained with slower communication channels compared to transmission of uncompressed images.

The increasing mobility of the population and frequent changes in healthcare coverage, in both the government and private sectors, require integration of medical records not only longitudinally, but also across a variety of healthcare providers. Early in 1998, the federal government decided to solve this problem by constructing a framework for access to medical records by all of the government's health care facilities, called the Government Computer-Based Patient Record (GCPR). The government consortium chose a proposal by Litton PRC, a partnership of 11 companies with complementary areas of expertise. The framework is based on open systems, which use publicly available standards, and includes a Master Patient Information Locator that allows access to medical information from remote facilities, based on creating a unique identifier for each and every individual patient. PRC will use the Digital Imaging and Communications in Medicine (DICOM) imaging standard for radiology, supplemented by Health Level Seven (HL7).

Image storage, display, and distribution have been difficult problems in radiology for many years. As improvements in technology have changed the nature of the storage and display media, demand for image portability, faster image acquisition, and flexible image distribution is driving the development of responsive systems. Technology, such as the wavelet-based multiresolution seamless image database (MrSID) portable image format (PIF), is enabling image management solutions that address the shifting "point-of-care." The MrSID PIF employs seamless, multiresolution technology, which allows the viewer to determine the size of the image to be viewed, as well as the position of the viewing area within the image dataset. In addition the MrSID PIF allows control of the compression ratio of decompressed images. This capability offers the advantage of very rapid image recall from storage devices and portability for rapid transmission and distribution using the internet or wide-area networks. For example, in teleradiology, the radiologist or other physician desiring to view images at a remote location has full flexibility in being able to choose a quick display of an overview image, a complete display of a full diagnostic quality image, or both without compromising communication bandwidth. The MrSID algorithm will satisfy Joint Photographic Experts Group (JPEG) 2000 standards, thereby being compatible with future versions of the Digital Imaging and Communications in Medicine (DICOM) standard for image data compression.

In recent years there have been many significant developments in the ability to process radiographic pictures and transfer the images from one location to another, and we can now examine the application of computers in the radiographic evaluation of rheumatoid arthritis. Image management and communication systems can assist in providing better health care while lowering costs. Although this work is still in its infancy, the rapid growth in both hardware capability and software techniques will soon make these techniques available to physicians everywhere. The expanding capability in the commercial world is being embraced by the radiology department, and will soon allow rheumatologists to access images at greater distances, and do more with the images which become available.

Computers have greatly facilitated the processing and storage of radiologic information. Manufacturers of radiology information systems (RISs) are gradually incorporating options for interfacing their products with other computers (e.g., hospital information systems). However, a growing need exists to also interface RISs with digital radiologic equipment so that images (e.g., computed radiographs of the chest and skeleton) are automatically labeled with identification data. Such connectivity would eliminate redundant work by technologists, decrease errors in the labeling of images, and increase the consistency of patients' data within a radiology department. Unfortunately, the rapid advances in digital technology, combined with the lack of a well-defined standard for the transfer of demographic information between dissimilar systems, have delayed development of these interfaces. We have developed a widely applicable method to automatically transfer patients' demographic data from an RIS to a commercially available computed radiography system. A personal computer is configured with inexpensive programmable telecommunications software to create an interactive gateway, which eliminates the need for redundant data entry (compared with entering data once on the RIS and again on the stand-alone computed radiography system), and thus also decreases errors in the labeling of images.

The authors have developed a new classified vector quantizer (CVQ) using decomposition and prediction which does not need to store or transmit any side information. To obtain better quality in the compressed images, human visual perception characteristics are applied to the classification and bit allocation. This CVQ has been subjectively evaluated for a sequence of X-ray CT images and compared to a DCT coding method. Nine X-ray CT head images from three patients are compressed at 10:1 and 15:1 compression ratios and are evaluated by 13 radiologists. The evaluation data are analyzed statistically with analysis of variance and Tukey's multiple comparison. Even though there are large variations in judging image quality among readers, the proposed algorithm has shown significantly better quality than the DCT at a statistical, significance level of 0.05. Only an interframe CVQ can reproduce the quality of the originals at 10:1 compression at the same significance level. While the CVQ can reproduce compressed images that are not statistically different from the originals in quality, the effect on diagnostic accuracy remains to be investigated.

Rationale and Objectives: The compression of cranial computed tomography scans was improved by using independent intra- and interframe compression techniques., Methods: For intraframe compression, an image was decomposed into four subimages, one subimage was chosen as a reference subimage, and three of the subimages were predicted from the reference subimage. The prediction error was encoded with a classified vector quantizer (CVQ) based on human visual perception characteristics. Interframe redundancy is exploited by a displacement estimated interslice (DEI) algorithm that encodes the differences between reference subimages from adjacent slices. This combined DEI/CVQ method was subjectively evaluated by 13 radiologists under a blinded protocol, and was compared to the CVQ method alone, the DEI method alone, the original images, and to a standard intraframe discrete cosine transform (DCT) compression method., Results: Only the combined DEI/CVQ method at 10:1 compression was not scored significantly different from the original images. At 15:1 compression, the DEI/CVQ method was scored significantly better than the 10:1 DCT and any other 15:1 compression methods., Conclusions: Compressed image quality is enhanced by exploiting inter- and intraframe redundancy, and by modeling some characteristics of human visual perception. The DEI/CVQ method is well-suited for progressive transmission, and thus, holds potential in teleradiology as well as picture archiving and communications systems.

This is the fifth and final article in our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers (PCs). There are many methods of transferring radiologic images into a PC, including transfer over a network, transfer from an imaging modality storage archive, using a frame grabber in the image display console, and digitizing a radiograph or 35-mm slide. Depending on the transfer method, the image file may be an extended gray-scale contrast, 16-bit raster file or an 8-bit PC graphics file. On the PC, the image can be viewed, analyzed, enhanced, and annotated. Some specific uses and applications include making 35-mm slides, printing images for publication, making posters and handouts, facsimile (fax) transmission to referring clinicians, converting radiologic images into medical illustrations, creating a digital teaching file, and using a network to disseminate teaching material. We are distributing a 16-bit image display and analysis program for Macintosh computers, Dr Razz, that illustrates many of the principles discussed in this review series. The program is available for no charge by anonymous file transfer protocol (ftp).

This is the fourth article of our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers. Classic image processing is divided into point, area, frame, and geometric processes. Point processes change image pixel values based on the value of the pixel of interest. Histogram equalization adjusts the pixel values in the image based on the distribution of pixel values. Area processes change the pixel of interest based on the values of the surrounding pixels, known as the neighborhood. Area processes using a convolution kernel are often used as image filters. Common convolution kernels include low-frequency, high-frequency, and edge-enhancement filters. Edge enhancement can be performed with convolution kernels such as shift and difference, gradient-directional and Laplacian filters, or with nonlinear methods such as Sobel's algorithm. Frame processes mathematically combine two or more images, often for noise reduction and background subtraction. Geometric processes alter the location of pixels within the image, but usually not the pixel values. Common radiologic applications of image processing include window width and window level adjustments (point process), adaptive histogram equalization (area process), unsharp masking (area process), computed radiography image processing (combined area and point processes), digital subtraction angiography (frame and geometric processes), region of interest analysis (area process), and image rotation (geometric process). As digital imaging becomes more widespread, radiologists need to understand the image processing that is fundamental to these modalities.

This is part 2 of our article on image storage and compression, the third article of our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers. Image compression is classified as lossless (nondestructive) or lossy (destructive). Common lossless compression algorithms include variable-length bit codes (Huffman codes and variants), dictionary-based compression (Lempel-Ziv variants), and arithmetic coding. Huffman codes and the Lempel-Ziv-Welch (LZW) algorithm are commonly used for image compression. All of these compression methods are enhanced if the image has been transformed into a differential image based on a differential pulse-code modulation (DPCM) algorithm. The LZW compression after the DPCM image transformation performed the best on our example images, and performed almost as well as the best of the three commercial compression programs tested. Lossy compression techniques are capable of much higher data compression, but reduced image quality and compression artifacts may be noticeable. Lossy compression is comprised of three steps: transformation, quantization, and coding. Two commonly used transformation methods are the discrete cosine transformation and discrete wavelet transformation. In both methods, most of the image information is contained in a relatively few of the transformation coefficients. The quantization step reduces many of the lower order coefficients to 0, which greatly improves the efficiency of the coding (compression) step. In fractal-based image compression, image patterns are stored as equations that can be reconstructed at different levels of resolution.

Most digital radiologic images have an extended contrast range of 9 to 13 bits, and are stored in memory and disk as 16-bit integers. Consequently, it is difficult to view such images on computers with 8-bit red-green-blue (RGB) graphic systems. Two approaches have traditionally been used: (1) perform a one-time conversion of the 16-bit image data to 8-bit gray-scale data, and then adjust the brightness and contrast of the image by manipulating the color palette (palette animation); and (2) use a software lookup table to interactively convert the 16-bit image data to 8-bit gray-scale values with different window width and window level parameters. The first method can adjust image appearance in real time, but some image features may not be visible because of the lack of access to the full contrast range of the image and any region of interest measurements may be inaccurate. The second method allows "windowing" and "leveling" through the full contrast range of the image, but there is a delay after each adjustment that some users may find objectionable. We describe a method that combines palette animation and the software lookup table conversion method that optimizes the changes in image contrast and brightness on computers with standard 8-bit RGB graphic hardware--the dual lookup table algorithm. This algorithm links changes in the window/level control to changes in image contrast and brightness via palette animation.(ABSTRACT TRUNCATED AT 250 WORDS)

The emerging widespread adoption of the Digital Imaging Communications in Medicine (DICOM) standard will increase the demand for radiologic image transfer between radiologic image acquisition, archive, display and printing devices. Unfortunately, there are and will continue to be many devices that do not and will not support this standard, especially older radiologic equipment and devices from nonradiologic vendors. Determining the image file format characteristics of images from such equipment is often difficult, and done on an ad hoc basis. We have developed a software tool that assists users in determining the image file format parameters of unknown radiologic images.

An increasing number of radiology departments are using computers to facilitate management of radiologic information. Transcription, storage, and printing of radiologic reports are among the primary functions of a radiology information system. Consequently, manual signature of radiologic reports is being replaced by on-line electronic authentication. However, the utilities provided on most radiology information systems to review, edit, and otherwise manipulate radiologic reports are relatively crude compared with commercial word-processing and data-base management software available for personal computers. We have developed a personal computer software system that is integrated with our existing radiology information system; expedites the radiologist's task of reviewing, editing, and authenticating (i.e., signing) radiologic reports; provides a teaching file data base on the workstation into which radiologic reports and patients' demographics can be instantly transferred; and provides a similar data base to facilitate follow-up on those examinations deemed appropriate for quality-assurance procedures. These features improve the radiologist's efficiency and increase his or her willingness to more fully exploit the intended purposes of a radiology information system.

This is the third article of our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers. Part 1 of this article discusses image storage and reviews the basic concepts of information theory and image compression; part 2 will discuss specific methods of image compression. There are a wide variety of removable storage devices available to users who need to archive radiologic images on their personal computers. Tape drives have potentially very large storage capacity but slow performance. Removable SyQuest (SyQuest Technology, Femont, CA) and Bernoulli disks have near hard disk performance and can store from 100 to 150 Mbytes. Magneto-optical drives can store nearly 1 Gb on a 5.25" disk, with somewhat slower performance. Selecting the most appropriate storage solution requires a careful balance of the user's requirements, including performance, storage needs, cost and compatibility with other users. Despite the advances in low cost high capacity storage technology, image compression remains a crucial technology for modern diagnostic radiology because digital images require such large amounts of storage. Image compression is possible because radiologic images have relatively low entropy (high information content) compared with random noise. Image compression is classified as lossless (nondestructive) or lossy (destructive). Lossless image compression commonly achieve compression ratios of 1.5:1 to 3:1 (33% to 67%), whereas lossy compression can compresses images from 3:1 to 30:1 (67% to 97%).(ABSTRACT TRUNCATED AT 250 WORDS)

Rationale and Objectives: The authors developed and subjectively evaluated an interslice compression algorithm that explores the redundancy among adjacent slices of an x-ray computed tomography (CT) scan. This algorithm has been compared to an intraslice compression algorithm based on the two-dimensional discrete cosine transform., Methods: Nine x-ray CT head images from three patients were compressed with this interslice method at compression ratios of 5:1, 10:1, and 15:1. The same images were also compressed with the intraslice method at the same ratios. Six radiologists judged quality of randomly selected compressed and decompressed images compared to that of the originals. The evaluation data were analyzed statistically with the analysis of variance and Tukey's multiple comparison. Kappa-like statistics (Williams index and O'Connell and Dobson indexes) were also calculated to measure the agreement among readers beyond the amount expected by chance., Results: The interslice coding algorithm showed significantly better quality than the intraslice method at significance level 0.05, even though there was no difference in the objective distortion measure (signal-to-noise ratio). Also, the quality of 10:1 compressed images with the interslice coding algorithm was not significantly different from that of the originals at level 0.05. While large variations in agreement occurred among readers, the overall agreement was statistically significant., Conclusions: By using adjacent slice information in compressing x-ray CT images, significantly better quality in compressed and decompressed images was achieved. While 10:1 compressed images with the interslice algorithm were not significantly different from the originals in quality at level 0.05, effect on diagnostic accuracy remains to be investigated.

This series of articles will explore the issue related to displaying, manipulating, and analyzing radiological images on personal computers (PC). This first article discusses the digital image data file, standard PC graphic file formats, and various methods for importing radiological images into the PC.

Displacement estimated interframe (DEI) coding, a coding scheme for 3-D medical image data sets such as X-ray computed tomography (CT) or magnetic resonance (MR) images, is presented. To take advantage of the correlation between contiguous slices, a displacement-compensated difference image based on the previous image is encoded. The best fitting distribution functions for the discrete cosine transform (DCT) coefficients obtained from displacement compensated difference images are determined and used in allocating bits and optimizing quantizers for the coefficients. The DEI scheme is compared with 2-D block discrete cosine transform (DCT) as well as a full-frame DCT using the bit allocation technique of S. Lo and H.K. Huang (1985). For X-ray CT head images, the present bit allocation and quantizer design, using an appropriate distribution model, resulted in a 13-dB improvement in the SNR compared to the full-frame DCT using the bit allocation technique. For an image set with 5-mm slice thickness, the DEI method gave about 5% improvement in the compression ratio on average and less blockiness at the same distortion. The performance gain increases to about 10% when the slice thickness decreases to 3 mm.

Radiology reports are likely to be more useful if they contain appropriate graphic material. Diagnostic conclusions and recommendations become more convincing and useful when the clinician personally can review the image on which these are based. Modern desk-top publishing techniques make it possible to incorporate radiographic images, appropriately selected and annotated, as part of the radiology report. It is believed that such illustrated reports would be preferred by referring physicians, notwithstanding a significant loss of image detail. A survey of these referring physicians was carried out to determine whether this hypothesis was correct.

A digital radiography system based on reusable, photostimulable phosphor technology was evaluated in approximately 3,500 portable chest radiographs of patients in an intensive care unit. The system functioned well in this application. No major problems were encountered in the visualization of tubes or catheters or in the detection of pneumothoraces. Assessment of fluid volume status or the presence of small pleural effusions, especially when these were bilateral, was initially somewhat difficult but became easier as investigators became familiar with the system. Radiologists were quicker than nonradiologists to accept the minimized two-on-one display format. Critical evaluation of the overall performance of digital systems such as this one is needed for a better definition of the system's strengths and weaknesses. Specifically, statistical analyses of the ability to detect disease states such as pneumothoraces, interstitial lung disease, lung nodules, and pleural abnormalities need to be performed.

CORRELATE is a new computer software program for CT that enables a radiologist to mark tumor margins on traditional CT cross-sectional images and then display the outline of that same tumor on CT ScoutView images. This function is particularly useful for radiation therapy planning because CORRELATE ScoutView images are in the same longitudinal plane as simulation radiographs used for tumor localization in radiation therapy. The impact of CORRELATE on the radiation therapy planning process was measured in 83 patients with various tumors. Therapy planning was performed before and after CORRELATE information was made available to the radiation therapist. CORRELATE information caused a change in the therapy plan in 77% of the cases and increased confidence in the therapy plan in an additional 22%. CORRELATE provides a useful and accurate tool for tumor localization.

The minicomputer that is part of a commercial CT scanner has been used to develop a general purpose computer-assisted education system. This allows instruction in radiology using the CT computer already installed in the radiology department. The computer software was designed as a course interpreter, allowing the courses themselves to be written in English. Images and educational text are stored on separate disk files and displayed by the interpreter.

Virus population dynamics in the lungs, trachea, and nasopharynx of Swiss-ICR mice were studied after respiratory challenge with mouse-adapted preparations of strain A2/Aichi/2/68 influenza virus. Markedly higher doses of virus were required to produce infection with nasopharyngeal challenge than with bronchoalveolar challenge. In all of the infections, the highest virus concentrations were observed in the lungs. Peak concentrations in the trachea were lower than in the lungs but higher than in the nasopharynx. Decreasing virus levels were observed by 120 h after challenge and were generally below detectable levels by the end of 10 days. A compartmental model of a single mathematical form was developed which provided close fits of the virus concentration measurements regardless of the challenge dose, site of initial deposition, or respiratory tissue considered. The model includes seven compartments with five associated rate parameters. The application of compartmental modeling techniques and expression of the virus population dynamics in mathematical terms is regarded as a new approach to the study of the pathogenesis of infections.

Mechanisms producing hypertriglyceridemia during bacterial sepsis have not been well defined. In this study lipid disposal mechanisms were assessed in 76 infected and 19 control male rhesus monkeys by the ability to dispose of triglycerides after: (1) oral lipid loading; (2) intravenous lipid loading; and (3) by lipolytic enzyme activity tests as measured by postheparin lipolytic activity (PHLA). Studies were performed both before and 48 hr after intravenous inoculation with either Salmonella typhimurium or Diplococcus pneumoniae when illness was uniformly severe and fasting serum triglyceride elevations were increased maximally. S. typhimurium-infected monkeys demonstrated significant fasting hypertriglyceridemia (p is less than 0.001), reduced clearance of orally and intravenously administered lipid and markedly reduced PHLA. During this gram-negative sepsis, mild lethargy, slight diarrhea, and a 2% mortality were observed. During D. pneumoniae sepsis, average fasting triglyceride concentrations were slightly, but not significantly elevated. While oral lipid clearance was impaired, intravenous lipid clearance was unimpaired, and PHLA was slightly reduced. Marked lethargy, agitation, and a 20% mortality were present during this gram-positive infection. Results of this study support the concept that an impairment of lipid disposal mechanisms, particularly during gram-negative sepsis with S. typhimurium, may significantly contribute to the observed hypertriglyceridemia.

How much does one need to know about the computer part of a computed tomographic or nuclear magnetic resonance system to select the best system and to use it effectively? Enough to comprehend how features or options relate to individual applications and needs. Besides acquiring some basic knowledge, one needs to consider upgradability, word size, and features of the image display controller, graphic input, array processor, and other hardware.

A computer software program (Seapit) was developed for precise determination of intracranial targets identified by stereotactic computed tomography (CT). This program was added to the software of a GE 8800 CT scanner to perform the following operations: millimetre precise calculation and display of the rectilinear coordinates of a target identified on axial CT images; preplotting of phantom target trajectories on the CT images or electronic radiographs; calculation of probe angles required to achieve various trajectories; display of a coordinate scale on each CT image to allow direct target determination without mathematical calculations; calculation of the intercommissural plane for functional neurosurgery. In a series of 100 patients undergoing stereotactic surgery, the Seapit program proved to be a superior and accurate method of target coordinate calculation. Preview display on the CT images of 'phantom' probes significantly enhanced the safety of stereotactic intervention.