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PubMedDate not supplied

A cryptologic based trust center for medical images.

OBJECTIVE: To investigate practical solutions that can integrate cryptographic techniques and picture archiving and communication systems (PACS) to improve the security of medical images. DESIGN: The PACS at the University of California San Francisco Medical Center consolidate images and associated data from various scanners into a centralized data archive and transmit them to remote display stations for review and consultation purposes. The purpose of this study is to investigate the model of a digital trust center that integrates cryptographic algorithms and protocols seamlessly into such a digital radiology environment to improve the security of medical images. MEASUREMENTS: The timing performance of encryption, decryption, and transmission of the cryptographic protocols over 81 volumetric PACS datasets has been measured. Lossless data compression is also applied before the encryption. The transmission performance is measured against three types of networks of different bandwidths: narrow-band Integrated Services Digital Network, Ethernet, and OC-3c Asynchronous Transfer Mode. RESULTS: The proposed digital trust center provides a cryptosystem solution to protect the confidentiality and to determine the authenticity of digital images in hospitals. The results of this study indicate that diagnostic images such as x-rays and magnetic resonance images could be routinely encrypted in PACS. However, applying encryption in teleradiology and PACS is a tradeoff between communications performance and security measures. CONCLUSION: Many people are uncertain about how to integrate cryptographic algorithms coherently into existing operations of the clinical enterprise. This paper describes a centralized cryptosystem architecture to ensure image data authenticity in a digital radiology department. The system performance has been evaluated in a hospital-integrated PACS environment.

Algorithms↗

PubMed1999

Distributing digital imaging and communications in medicine data and optimizing access over satellite networks.

To improve radiology access to full uncompressed Digital Imaging and Communications in Medicine (DICOM) data sets, we evaluated satellite access to a DICOM server. Radiologists' home computers were connected by satellite to a Medweb DICOM server (Medweb, San Francisco, CA). A 10.2-kb data set containing a 19-image head computed tomography (CT) scan was transferred using DirecPC (Hughes Electronics Corp, Arlington, VA) at three different times of the day; 6 AM, 3 PM, and 8 PM. The average transfer time for all 19 images from the DICOM server was 4 minutes and 17 seconds (257 seconds). The slowest transfer rate of 670 seconds (121 kbps) was obtained at 8 PM. The best transfer rate of 2 minutes, 54 seconds (467 kbps) was obtained at 6 AM. The full 16-bit DICOM images were viewed with bone, brain, and soft tissue windows. The Medweb plug-in viewer loaded the first image within 30 seconds of selecting the case for satellite transfer. In conclusion, satellite internet transfer of radiology studies is suitable for timely review of full DICOM data sets and can expand the range of teleradiology consultation.

Brain↗

PubMed1998

Coordinated force production in multi-finger tasks: finger interaction and neural network modeling.

During maximal voluntary contraction (MVC) with several fingers, the following three phenomena are observed: (1) the total force produced by all the involved fingers is shared among the fingers in a specific manner (sharing); (2) the force produced by a given finger in a multi-finger task is smaller than the force generated by this finger in a single-finger task (force deficit); (3) the fingers that are not required to produce any force by instruction are involuntary activated (enslaving). We studied involuntary force production by individual fingers (enslaving effects, EE) during tasks when (an)other finger(s) of the hand generated maximal voluntary pressing force in isometric conditions. The subjects (n = 10) were instructed to press as hard as possible on the force sensors with one, two, three and four fingers acting in parallel in all possible combinations. The EE were (A) large, the slave fingers always producing a force ranging from 10.9% to 54.7% of the maximal force produced by the finger in the single-finger task; (B) nearly symmetrical; (C) larger for the neighboring fingers; and (D) non-additive. In most cases, the EE from two or three fingers were smaller than the EE from at least one finger (this phenomenon was coined occlusion). The occlusion cannot be explained only by anatomical musculo-tendinous connections. Therefore, neural factors contribute substantially to the EE. A neural network model that accounts for all the three effects has been developed. The model consists of three layers: the input layer that models a central neural drive; the hidden layer modeling transformation of the central drive into an input signal to the muscles serving several fingers simultaneously (multi-digit muscles); and the output layer representing finger force output. The output of the hidden layer is set inversely proportional to the number of fingers involved. In addition, direct connections between the input and output layers represent signals to the hand muscles serving individual fingers (uni-digit muscles). The network was validated using three different training sets. Single digit muscles contributed from 25% to 50% of the total finger force. The master matrix and the enslaving matrix were computed; they characterize the ability of a given finger to enslave other fingers and its ability to be enslaved. Overall, the neural network modeling suggests that no direct correspondence exists between neural command to an individual finger and finger force. To produce a desired finger force, a command sent to an intended finger should be scaled in accordance with the commands sent to the other fingers.

Adult↗

PubMed2006

Computer-aided diagnosis of emphysema in COPD patients: neural-network-based analysis of lung shape in digital chest radiographs.

Several abnormalities of the shape of lung fields (depression and flattening of the diaphragmatic contours, increased retrosternal space) are indicative of emphysema and can be accurately imaged by digital chest radiography. In this work, we aimed at developing computational descriptors of the shape of the lung silhouette able to capture the alterations associated with emphysema. We analyzed two-sided digital chest radiographs from a sample of 160 patients with chronic obstructive pulmonary disease (COPD), 60 of which were affected by emphysema, and from 160 subjects with normal lung function. Two different description schemes were considered: a first one based on lung-silhouette curvature features, and a second one based on a minimal-polyline approximation of the lung shape. Both descriptors were employed to recognize alterations of the lung shape using classifiers based on multilayer neural networks of the feed-forward type. Results indicate that pulmonary emphysema can be reliably diagnosed or excluded by using digital chest radiographs and a proper computational aid. Two-sided chest radiographs provide more accurate discrimination than single-view analysis. The minimal-polyline approximation provided significantly better results than those obtained from curvature-based features. Emphysema was detected, in the entire dataset, with an accuracy of about 90% (sensitivity 88%, specificity 90%) by using the minimal-polyline approximation.

Humans↗

PubMed2000

Secure remote access to a clinical data repository using a wireless personal digital assistant (PDA).

TCP/IP and World-Wide-Web (WWW) technology have become the universal standards for networking and delivery of information. Personal digital assistants (PDAs), cellular telephones, and alphanumeric pagers are rapidly converging on a single pocket device that will leverage wireless TCP/IP networks and WWW protocols and can be used to deliver clinical information and alerts anytime, anywhere. We describe a wireless interface to clinical information for physicians based on Palm Corp.'s Palm VII pocket computer, a wireless digital network, encrypted data transmission, secure web servers, and a clinical data repository (CDR).

Computer Security↗

PubMed2005

An evaluation of a surgical telepresence system for an intrahospital local area network.

We evaluated a digital telepresence system in an operating theatre (OR) environment which enabled a consultant to join the surgical team from a remote site by audiovisual communication. The system is based on video transmission using a streaming technique, with a server and a client connected via a local area network (LAN). Two cameras can be remotely controlled: one camera is built into the OR lamp and a second, laparoscopic camera is mounted on a robotic arm. Another feature of the system is teledemonstration, which permits the remote consultant to demonstrate points of particular interest. We evaluated the system clinically in 237 cases. In 28 cases (12%), telepresence could not be established for various reasons, mainly human failure. In 42 cases (18%), the full potential of telepresence was used. Technical evaluation showed that a data rate of 2 Mbit/s provides sufficient audio and video quality, as well as reliable teledemonstration. The data transmission delay was acceptable for clinical purposes (video 0.92 s, audio 0.6 s from OR to client, audio 0.7 s from client to OR). The study showed that telepresence is a promising means of providing highly specialized expertise within the OR.

General Surgery↗

PubMedDate not supplied

Virtual shelves in a digital library: a framework for access to networked information sources.

OBJECTIVE: Develop a framework for collections-based access to networked information sources that addresses the problem of location-dependent access to information sources. DESIGN: This framework uses a metaphor of a virtual shelf. A virtual shelf is a general-purpose server that is dedicated to a particular information subject class. The identifier of one of these servers identifies its subject class. Location-independent call numbers are assigned to information sources. Call numbers are based on standard vocabulary codes. The call numbers are first mapped to the location-independent identifiers of virtual shelves. When access to an information resource is required, a location directory provides a second mapping of these location-independent server identifiers to actual network locations. RESULTS: The framework has been implemented in two different systems. One system is based on the Open System Foundation/Distributed Computing Environment and the other is based on the World Wide Web. CONCLUSIONS: This framework applies in new ways traditional methods of library classification and cataloging. It is compatible with two traditional styles of selecting information searching and browsing. Traditional methods may be combined with new paradigms of information searching that will be able to take advantage of the special properties of digital information. Cooperation between the library-informational science community and the informatics community can provide a means for a continuing application of the knowledge and techniques of library science to the new problems of networked information sources.

Catalogs, Library↗

PubMed1993

Application of artificial neural networks for reduction of false-positive detections in digital chest radiographs.

A methodology based on the fuzzy set theory and the convolution neural network (CNN) architecture is proposed to tackle the problem of reducing false-positive rate in automatic lung nodule detection. The CNN which simulates human visual mechanism was trained by a supervised back-propagation algorithm based on fuzzy membership functions. The training and testing database consists of image blocks (each 32 x 32 pixels) of suspected lung nodule areas (nodule candidates) which were generated from our pre-scanning program [1]. A linguistic label was assigned to each nodule candidate of the training set, then the label was converted to a membership value through a pre-defined membership function and used as teaching signal (desired outputs) during the network learning. Before the nodule candidate was fed to the network input, it was pre-processed to reduce the complex background noise and the contrast discrepancy resulted from film development. During the network testing phase, a defuzzification process was applied to decipher the trained network's output triggered by the nodule candidate in the testing set. Finally, a Receiver Operating Characteristic (ROC) analysis was used to evaluate the CNN's performance based on the defuzzified output of the testing database. Preliminary results showed an average Az (the performance index) of 0.84 which is equivalent to 0.80 true-positive detection (sensitivity) with an average 2-3 false-positive detections per chest image.

Computer Simulation↗

PubMed1994

Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network.

A computer-aided diagnosis (CAD) scheme has been developed in our laboratory for the detection of clustered microcalcifications in digital mammograms. In this study, we apply a shift-invariant neural network to eliminate false-positive detections reported by the CAD scheme. The shift-invariant neural network is a multilayer back-propagation neural network with local, shift-invariant interconnections. The advantage of the shift-invariant neural network is that the result of the network is not dependent on the locations of the clustered microcalcifications in the input layer. The neural network is trained to detect each individual microcalcification in a given region of interest (ROI) reported by the CAD scheme. A ROI is classified as a positive ROI if the total number of microcalcifications detected in the ROI is greater than a certain number. The performance of the shift-invariant neural network was evaluated by means of a jackknife (or holdout) method and ROC analysis using a database of 168 ROIs, as reported by the CAD scheme when applied to 34 mammograms. The analysis yielded an average area under the ROC curve (Az) of 0.91. Approximately 55% of false-positive ROIs were eliminated without any loss of the true-positive ROIs. The result is considerably better than that obtained in our previous study using a conventional three-layer, feed-forward neural network. The effect of the network structure on the performance of the shift-invariant neural network is also studied.

Biophysical Phenomena↗

PubMedDate not supplied

Computer aided diagnosis of breast cancer in digitized mammograms.

A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this paper which employs features extracted by a new technique based on independent component analysis. Our approach is concentrated in finding a set of independent source regions that generate the observed mammograms. The coefficients of the linear transformation of the source regions are used as features that describe effectively any normal and abnormal region in digital mammograms as well as benign and malignant ROS in the latter case. Extensive experiments in the MIAS Database have shown a recognition accuracy of 88.23% in the detection of all kinds of abnormalities and 79.31% in the task of distinguishing between benign and malignant regions, outperforming in both cases standard textural features, widely used for cancer detection in mammograms.

Breast Diseases↗

PubMed1986

Transmitting deaf sign language over the telecommunications network.

An experimental investigation is reported into the use of moving cartoon images for two-way communication by the deaf. The images are derived by special signal-processing operations on the output of a conventional television camera, according to a new theory of perceptually important human features. Calculations show that, using facsimile-type coding and digital modems, the images are capable of transmission over the Public Switched Telephone Network; in enhanced form (with more resolution and optional voice accompaniment) they could be carried on the emerging Integrated Services Digital Network or transmitted over teletext.

Communication Devices for People with Disabilities↗

PubMed2006

Pharmacologic transgene control systems for gene therapy.

Pharmacologic transgene-expression dosing is considered essential for future gene therapy scenarios. Genetic interventions require precise transcription or translation fine-tuning of therapeutic transgenes to enable their titration into the therapeutic window, to adapt them to daily changing dosing regimes of the patient, to integrate them seamlessly into the patient's transcriptome orchestra, and to terminate their expression after successful therapy. In recent years, decisive progress has been achieved in designing high-precision trigger-inducible mammalian transgene control modalities responsive to clinically licensed and inert heterologous molecules or to endogenous physiologic signals. Availability of a portfolio of compatible transcription control systems has enabled assembly of higher-order control circuitries providing simultaneous or independent control of several transgenes and the design of (semi-)synthetic gene networks, which emulate digital expression switches, regulatory transcription cascades, epigenetic expression imprinting, and cellular transcription memories. This review provides an overview of cutting-edge developments in transgene control systems, of the design of synthetic gene networks, and of the delivery of such systems for the prototype treatment of prominent human disease phenotypes.

Animals↗

PubMed2003

Predicting the behaviour of G-RAM networks.

A Generalising Random Access Memory (G-RAM) neuron is distinguished from conventional neuron models by the fact that its tolerance to departures in similarity from its training pattern is variable. Details of this are given in this paper as it affects the behaviour a class of digital probabilistic neural networks which have been achieving attention in the neural networks literature for some years now. Such systems are also called n-tuple systems, weightless systems or p-RAM systems. After reviewing the literature on such networks, a novel simple combinatoric analysis of the most likely behaviour of recursive GRAM networks is described. The best network performance, measured by a key parameter called 'radius of retrievability' (first defined by Wong and Sherrington [J. Phys. A 22 (1989) 2233] as the error in the input that still allows evolution of the dynamic network to the correct attractor state), is obtained with a training set composed of random data patterns. Increasing the size of the training set reduces this radius of retrievability in a predictable manner. Changing the nature of the training set to non-random patterns also reduces the radius of retrievability to an extent that we show can be estimated from a measure of the diversity of the elements of the training set (we refer to this as the 'mean intra-set Hamming distance of the training set'). As mentioned earlier the feature of G-RAMs (indicated by the G) is that there exists a generalization parameter which determines how far a neuron input vector can stray from a training input for the neuron to respond in the trained way. It is shown that when this generalization parameter is reduced, then the radius of retrievability is also reduced but it is then stable in the face of an increase in size, or change in nature, of the training set. This is a novel prediction of the behaviour of systems and of the robustness of such behaviour in the face of varying the size and correlation properties of the training set.

Algorithms↗

PubMed1988

A wide-band high-resolution spectrum analyzer.

This paper describes a two-million-channel 40-MHz-bandwidth, digital spectrum analyzer under development at the Jet Propulsion Laboratory. The analyzer system will serve as a prototype processor for the sky survey portion of NASA's Search for Extraterrestrial Intelligence program and for other applications in the Deep Space Network. The analyzer digitizes an analog input, performs a 2(21)-point, Discrete Fourier Transform, accumulates the output power, normalizes the output to remove frequency-dependent gain, and automates simple signal detection algorithms. Due to its built-in frequency-domain processing functions and configuration flexibility, the analyzer is a very powerful tool for real-time signal analysis and detection.

Algorithms↗

PubMed2004

Radiology: "killer app" for next generation networks?

The core principles of digital radiology were well developed by the end of the 1980 s. During the following decade tremendous improvements in computer technology enabled realization of those principles at an affordable cost. In this decade work can focus on highly distributed radiology in the context of the integrated health care enterprise. Over the same period computer networking has evolved from a relatively obscure field used by a small number of researchers across low-speed serial links to a pervasive technology that affects nearly all facets of society. Development directions in network technology will ultimately provide end-to-end data paths with speeds that match or exceed the speeds of data paths within the local network and even within workstations. This article describes key developments in Next Generation Networks, potential obstacles, and scenarios in which digital radiology can become a "killer app" that helps to drive deployment of new network infrastructure.

Computer Communication Networks↗

PubMed1999

Nonlinear Optics for High-Speed Digital Information Processing.

Recent advances in developing nonlinear optical techniques for processing serial digital information at high speed are reviewed. The field has been transformed by the advent of semiconductor nonlinear devices capable of operation at 100 gigabits per second and higher, well beyond the current speed limits of commercial electronics. These devices are expected to become important in future high-capacity communications networks by allowing digital regeneration and other processing functions to be performed on data signals "on the fly" in the optical domain.

Journal Article↗

PubMed2004

A hybrid hopfield network-simulated annealing approach for frequency assignment in satellite communications systems.

A hybrid Hopfield network-simulated annealing algorithm (HopSA) is presented for the frequency assignment problem (FAP) in satellite communications. The goal of this NP-complete problem is minimizing the cochannel interference between satellite communication systems by rearranging the frequency assignment, for the systems can accommodate the increasing demands. The HopSA algorithm consists of a fast digital Hopfield neural network which manages the problem constraints hybridized with a simulated annealing which improves the quality of the solutions obtained. We analyze the problem and its formulation, describing and discussing the HopSA algorithm and solving a set of benchmark problems. The results obtained are compared with other existing approaches in order to show the performance of the HopSA approach.

Journal Article↗

PubMed1995

[Image transmission between hospitals. Technical and clinical testing of the equipment for digital image transmission between hospitals via the ordinary telephone network].

A standard PC-based equipment--"Multiview Photophone"--for two-way image conference between hospitals by means of digital images transmitted through ordinary telephone lines was tested. The technical and visual quality of scanned and transmitted pictures proved to be satisfactory, and ease of handling the equipment and transmission times were acceptable. The clinical test was made by image conferences between a neurological department in a general hospital and a neurosurgical department in a university hospital. CT-scans concerning 39 patients in a prospective series, for whom specialist advice from the neurosurgical department was found necessary, were transmitted. Four of nine acute patients were saved an "unnecessary" transferral to the neurosurgical department. The 30 elective patients were all found to benefit from the two-way conferences, since the decision time was reduced and the quality of information given to the patients and their relatives was improved.

Computer Communication Networks↗