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Biomedical subjects

T Gillespy

Publications and source records attributed to T Gillespy.

At least 19 recordsLinked to original sources
PubMed1999

Viewing DICOM-compliant CT images on a desktop personal computer: use of an inexpensive DICOM receive agent and freeware image display applications.

OBJECTIVE: Our objective was to determine the ease of installation and use of relatively inexpensive and free software applications that allow Macintosh users to receive and view CT images from a Digital Imaging and COmmunication in Medicine-compliant imaging network. CONCLUSION: Simple-to-use Macintosh-based options to transfer and view images are readily available and easily installed by users with minimal computer expertise.

Humans↗
PubMed1996

Transforming growth factor-beta 1 in a guanidine-extracted demineralized bone matrix carrier rapidly closes a rabbit critical calvarial defect.

Transforming growth factor beta 1 (TGF-beta 1) is a polyfunctional regulatory cytokine that has been shown to have roles in extracellular matrix interactions, soft tissue healing, and osteogenesis. Twenty-five microL of recombinant human TGF-beta 1 was added to guanidine-extracted demineralized bone matrix carrier and the implants were used to fill a 14-mm osteoperiosteal critical calvarial defect in New Zealand white rabbit model. The defects were allowed to heal over 4 weeks and the degree of new bone formation was assess by radiodensitometry and undecalcified bone histomorphometry techniques. Implants with TGF-beta 1 showed complete bridging of the gap with new bone in all cases, while the controls showed fibrous tissue repair of the gap with little or no new bone formation. These results demonstrate the ability of TGF-beta 1 to induce new bone in a brief time period in an inactive carrier.

Animals↗
PubMed1995

Cortical bone perfusion in plated fractured sheep tibiae.

The limited contact dynamic compression plate and partial contact plate were designed to decrease contact with cortical bone in an attempt to decrease cortical ischemia, remodeling, and eventual porosis under the plate after use of standard dynamic compression plates. This study quantified cortical bone blood flow beneath the plate with these three different designs in a sheep tibia fracture model. In 18 skeletally immature sheep, the right tibia was fractured and then was internally fixed with an interfragmentary screw and a dynamic compression plate, limited contact dynamic compression plate, or partial contact plate. At 12 weeks, cortical bone perfusion was assessed with laser Doppler flowmetry in nine areas beneath the plate. The baseline (before fracture) cortical bone cell flux averaged 100 +/- 60 mV. After fracture, this decreased to 60 +/- 48 mV (p < 0.0003); immediately after plating, the perfusion averaged 29 +/- 25 mV (p < 0.01). Cortical bone perfusion then increased to 106 +/- 52, 165 +/- 71, and 163 +/- 71 mV at 2, 6, and 12 weeks after fracture (p < 0.001 for all when compared with values after plating). No significant differences in cortical perfusion were seen between the types of plate. Cortical porosity under the plate was assessed with digital density analysis of microradiographs of this region. No significant difference was seen between the types of plate in this analysis or in biomechanical and disulphine blue perfusion analysis. Thus, no significant advantage was seen for the new plate designs used in this model. This lack of advantage may be a result of the immature animals used in the study, the protocol for blood flow measurement, the invasive periosteal stripping employed to create the fracture, or all three. However, as advantages with the new plate designs have been seen in other studies, this area warrants further investigation.

Analysis of Variance↗
PubMed1994

Displaying radiologic images on personal computers: image processing and analysis.

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.

Algorithms↗
PubMed1994

Displaying radiologic images on personal computers: image storage and compression--Part 2.

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.

Algorithms↗
PubMed1994

Dual lookup table algorithm: an enhanced method of displaying 16-bit gray-scale images on 8-bit RGB graphic systems.

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)

Algorithms↗
PubMed1994

Displaying radiologic images on personal computers: practical applications and uses.

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).

Audiovisual Aids↗
PubMed1994

Functionality of gray-scale display workstation hardware and software in clinical radiology.

This article examines the functional factors crucial for the successful conversion from film-based radiography to radiologic gray-scale display systems, including hardware architecture and software requirements, radiologic workstation operations, and a multilayered intelligent user interface. Radiologic workstation operations are logically decomposed into case preparation, case selection, case presentation, case interpretation, and documentation and presentation of the diagnosis. A multilayered software architecture for an adaptive, intelligent user interface is proposed: a hardware interface layer, an object-oriented layer, and a knowledge-based layer. The knowledge-based layer is composed of three elements: image presentation based on context-dependent models of diagnostic requirements, knowledge-based expert systems for assistance in diagnostic decision making, and computer-assisted diagnosis to alert the radiologist to potential lesions or abnormalities.

Diagnosis, Computer-Assisted↗
PubMed1994

Dr. Browse, a digital image file format Browser.

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.

Analog-Digital Conversion↗
PubMed1993

Optimized algorithms for displaying 16-bit gray scale images on 8-bit computer graphic systems.

Most personal computers contain 8-bit graphic display hardware, whereas most medical gray scale images are stored at 16-bit per pixel integers. To display medical gray scale images on such computers, the 16-bit image data must be remapped into 8-bit gray scale images. This report presents the algorithms and computer code that allow very rapid 16-bit to 8-bit image data transformation. These algorithms are helpful in allowing personal computers with at least the performance of a Macintosh II (Apple Computer, Cupertino, CA) computer to function as low-end picture archiving communication systems or personal workstations.

Algorithms↗
PubMed1993

Displaying radiologic images on personal computers.

This is the second article of our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers (PCs). The first article discussed the digital image data file, standard PC graphic file formats, and various methods for importing radiologic images into the PC. This article discusses the hardware, software, and user interface issues related to displaying gray scale images on PCs. In particular, this segment focuses on the process of converting the digital image into gray shades on a color monitor. A method for displaying and interactively setting the window width and window level parameters of 16-bit radiologic images on PCs with standard red green blue graphic hardware is illustrated in a sample application.

Computer Graphics↗
PubMed1993

Displaying radiologic images on personal computers: image storage and compression: Part 1.

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)

Computer Storage Devices↗
PubMed1993

Advanced applications of personal computers in the radiologist's office.

The author's department has found various advanced applications for the computer to be useful in daily practice. They use a data-base program to track interesting cases for later retrieval. The program automatically generates an American College of Radiology code based on the body part and diagnosis. The program is also used to track radiographic film quality. A barcode scanner attached to a computer at the film alternator is used to enter the accession number generated by the radiology information system. If any deficiencies are present, they are entered from a preprinted bar-code sheet. The bar-code scanner allows rapid entry of all examinations during the read-out session. Reports generated from the data base have been helpful in identifying and quantifying radiographic examination deficiencies. Department computers are also connected to the campus Ethernet network. This network allows radiologists to electronically verify radiology reports and to conduct electronic literature searches on the computers in their offices.

Database Management Systems↗
PubMed1993

Quality assessment in radiology: value of a portable bar-code scanner integrated with a computer workstation.

Radiographs are typically processed by several employees of a radiology department before being interpreted by a radiologist. A technologist acquires and labels the radiograph(s), and file room employees match the radiograph(s) with prior examinations and prepare them for interpretation by the radiologist. Every radiologist has encountered radiologic examinations in which the image quality, presentation, or associated clinical or technical information is suboptimal. In small departments, the process of immediately tracking the problem to its source and correcting it might be straightforward, albeit an annoying interruption to the radiologist's focus on clinical care. However, in larger departments, trends of human error or machine malfunction may be overlooked or untraceable because no effective method exists to track the quality of images and associated information. A feedback loop from radiologists to the department's ancillary personnel can result in a cycle of continuous quality improvement that enhances the quality of radiographic examinations and also decreases waste. To achieve this, we designed and implemented a computerized process that involves a portable bar-code scanner, a personal computer workstation, and our existing radiology information system.

Electronic Data Processing↗
PubMed1993

Quality assurance: a system that integrates a digital dictation system with a computer data base.

One of the most challenging responsibilities for radiologists is assessment of the quality of care that they provide. Some parameters of quality, such as false-negative rate, are almost impossible to calculate with absolute precision. The issue is also complicated when one tries to determine exactly what constitutes a "discordant" interpretation. However, even when a radiologist discovers that a radiographic finding was missed, or that an inappropriate examination was done, the steps necessary to perform an analysis of the problem can be very disruptive to one's clinical focus at the moment. This suggests that a major obstacle to participation in quality assurance by radiologists is the lack of an adequate infrastructure. We have integrated our digital dictation system with a personal computer data base for tracking cases appropriate for quality assurance, thus allowing radiologists to log any examination from any dictation station in our department with minimal interruption to their clinical activities. Quality assurance and peer review are facilitated by using a personal computer for otherwise tedious aspects of information management. Radiology departments that have a convenient, department-wide method for entering cases--such as a digital dictation system--are ideal for this technique.

Humans↗