SNOMED CT module-driven clinical archetype management

ObjectiveTo explore semantic search to improve management and user navigation in clinical archetype repositories.MethodsIn order to support semantic searches across archetypes, an automated method based on SNOMED CT modularization is implemented to transform clinical archetypes into SNOMED CT extracts. Concurrently, query terms are converted into SNOMED CT concepts using the search engine Lucene. Retrieval is then carried out by matching query concepts with the corresponding SNOMED CT segments.ResultsA test collection of the 16 clinical archetypes, including over 250 terms, and a subset of 55 clinical terms from two medical dictionaries, MediLexicon and MedlinePlus, were used to test our method. The keyword-based service supported by the OpenEHR repository offered us a benchmark to evaluate the enhancement of performance. In total, our approach reached 97.4% precision and 69.1% recall, providing a substantial improvement of recall (more than 70%) compared to the benchmark.ConclusionsExploiting medical domain knowledge from ontologies such as SNOMED CT may overcome some limitations of the keyword-based systems and thus improve the search experience of repository users. An automated approach based on ontology segmentation is an efficient and feasible way for supporting modeling, management and user navigation in clinical archetype repositories.     

RayPlus: a Web-Based Platform for Medical Image Processing

Medical image can provide valuable information for preclinical research, clinical diagnosis, and treatment. As the widespread use of digital medical imaging, many researchers are currently developing medical image processing algorithms and systems in order to accommodate a better result to clinical community, including accurate clinical parameters or processed images from the original images. In this paper, we propose a web-based platform to present and process medical images. By using Internet and novel database technologies, authorized users can easily access to medical images and facilitate their workflows of processing with server-side powerful computing performance without any installation. We implement a series of algorithms of image processing and visualization in the initial version of Rayplus. Integration of our system allows much flexibility and convenience for both research and clinical communities.     

Automatic indexing and retrieval of encounter-specific evidence for point-of-care support

Evidence-based medicine relies on repositories of empirical research evidence that can be used to support clinical decision making for improved patient care. However, retrieving evidence from such repositories at local sites presents many challenges. This paper describes a methodological framework for automatically indexing and retrieving empirical research evidence in the form of the systematic reviews and associated studies from The Cochrane Library, where retrieved documents are specific to a patient–physician encounter and thus can be used to support evidence-based decision making at the point of care. Such an encounter is defined by three pertinent groups of concepts – diagnosis, treatment, and patient, and the framework relies on these three groups to steer indexing and retrieval of reviews and associated studies. An evaluation of the indexing and retrieval components of the proposed framework was performed using documents relevant for the pediatric asthma domain. Precision and recall values for automatic indexing of systematic reviews and associated studies were 0.93 and 0.87, and 0.81 and 0.56, respectively. Moreover, precision and recall for the retrieval of relevant systematic reviews and associated studies were 0.89 and 0.81, and 0.92 and 0.89, respectively. With minor modifications, the proposed methodological framework can be customized for other evidence repositories.     

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%). Many lossless compression methods are enhanced by first creating a difference image using discrete pulse code modulation. All compression methods are adversely affected by image noise.     

Computerized Analysis of Digital Subtraction Angiography: A Tool for Quantitative In-vivo Vascular Imaging

The purpose of our study was to develop a user-independent computerized tool for the automated segmentation and quantitative assessment of in vivo-acquired digital subtraction angiography (DSA) images. Vessel enhancement was accomplished based on the concept of image structural tensor. The developed software was tested on a series of DSA images acquired from one animal and two human angiogenesis models. Its performance was evaluated against manually segmented images. A receiver’s operating characteristic curve was obtained for every image with regard to the different percentages of the image histogram. The area under the mean curve was 0.89 for the experimental angiogenesis model and 0.76 and 0.86 for the two clinical angiogenesis models. The coordinates of the operating point were 8.3% false positive rate and 92.8% true positive rate for the experimental model. Correspondingly for clinical angiogenesis models, the coordinates were 8.6% false positive rate and 89.2% true positive rate and 9.8% false positive rate and 93.8% true positive rate, respectively. A new user-friendly tool for the analysis of vascular networks in DSA images was developed that can be easily used in either experimental or clinical studies. Its main characteristics are robustness and fast and automatic execution. Electronic supplementary material  The online version of this article (doi: ) contains supplementary material, which is available to authorized users.     

On the selection of systems for automated cytogenetic analysis

Impressive technological advances in systems for automated metaphase location and cytogenetic analysis have resulted in a proliferation of commercially available systems offering a variety of performance and price options. Based on the numbers of systems sold, it appears as if automation is becoming an accepted component of cytogenetic laboratories. To address the question of whether automation is useful and, if so, to identify the advantages and disadvantages of some of the systems, we have supplemented our own laboratory experience using the Magiscan routinely for clinical cytogenetic analysis, with information obtained during an on-site survey of other clinical cytogenetic facilities using automated systems (Genetiscan, Karyotype Image Editor, Metachrome, Cytoscan). Some systems provide both metaphase-locating and karyotyping capabilities--some only the latter. The basic structure of all systems is similar: microscope with camera, image processor, mechanism for operator interaction with the computer, hard copy printer. Metaphases are digitized, analyzed, and converted to permanent images. Metaphase-locating systems (Cytoscan, Magiscan, Metachrome) require, in addition, motorized slide-scanning stages. The biggest time savings resulting from use of automation is in the karyotyping steps, especially the production of a hard copy. Consequently, laboratories making many karyotypes will benefit most from such systems. The optimum choice of system will depend on specific laboratory parameters: number and type of specimens processed; operational preferences, e.g., number of bands per metaphase; number of metaphases counted; and karyotypes prepared per case. Laboratories processing chorionic villus specimens and/or bone marrows, where much slide area must be searched, will benefit from fast metaphase locators with multislide stages.(ABSTRACT TRUNCATED AT 250 WORDS)     

An automated patient recognition method based on an image-matching technique using previous chest radiographs in the picture archiving and communication system environment.

An automated patient recognition method for correcting "wrong" chest radiographs being stored in a picture archiving and communication system (PACS) environment has been developed. The method is based on an image-matching technique that uses previous chest radiographs. For identification of a "wrong" patient, the correlation value was determined for a previous image of a patient and a new, current image of the presumed corresponding patient. The current image was shifted horizontally and vertically and rotated, so that we could determine the best match between the two images. The results indicated that the correlation values between the current and previous images for the same, "correct" patients were generally greater than those for different, "wrong" patients. Although the two histograms for the same patient and for different patients overlapped at correlation values greater than 0.80, most parts of the histograms were separated. The correlation value was compared with a threshold value that was determined based on an analysis of the histograms of correlation values obtained for the same patient and for different patients. If the current image is considered potentially to belong to a "wrong" patient, then a warning sign with the probability for a "wrong" patient is provided to alert radiology personnel. Our results indicate that at least half of the "wrong" images in our database can be identified correctly with the method described in this study. The overall performance in terms of a receiver operating characteristic curve showed a high performance of the system. The results also indicate that some readings of "wrong" images for a given patient in the PACS environment can be prevented by use of the method we developed. Therefore an automated warning system for patient recognition would be useful in correcting "wrong" images being stored in the PACS environment.     

A FULLY AUTOMATED MICROSCOPE BACTERIAL ENUMERATION SYSTEM FOR STUDIES OF ORAL MICROBIAL ECOLOGY

A fast and fully automated image analysis technique for the enumeration of fluorescence-labeled bacteria in oral samples was developed. This paper describes the system configuration, application strategy, automated operation, and initial validation experiments using fluorescent microspheres, bacterial cultures, in vitro grown biofilms and human dental plaque. Following a series of brief operator-controlled calibration steps, the technique automatically performs all necessary microscope operations (stage translation, focus, sampling and analysis) on slides with up to 48 wells for as many different samples. It quantifies bacteria from differential interference contrast images, images showing cells that had been labeled by immunofluorescence with monoclonal antibodies, or images with cells labeled by a fluorescent DNA stain.

With all evaluated samples, close agreement between the automated system and the assessor's visual counts was observed. This novel automated image grabbing and analysis procedure is applicable to the enumeration of specific taxa in clinical samples by both immunofluorescence and fluorescent in situ hybridization.     

A fully automated microscope bacterial enumeration system for studies of oral microbial ecology

A fast and fully automated image analysis technique for the enumeration of fluorescence-labeled bacteria in oral sampleswas developed. This paper describes the system configuration, application strategy, automated operation, and initial validation experiments using fluorescent microspheres, bacterial cultures, in vitro grown biofilms and human dental plaque. Following a series of brief operator-controlled calibration steps, the technique automatically performs all necessary microscope operations (stage translation, focus, sampling and analysis) on slides with up to 48 wells for as many different samples. It quantifies bacteria from differential interference contrast images, images showing cells that had been labeled by immunofluorescence with monoclonal antibodies, or images with cells labeled by a fluorescent DNA stain. With all evaluated samples, close agreement between the automated system and the assessor's visual counts was observed. This novel automated image grabbing and analysis procedure is applicable to the enumeration of specific taxa in clinical samples by both immunofluorescence and fluorescent in situ hybridization.     

A general software package for the handling of medical images.

PICS (portable imaging computer software), is a software system designed for handling and processing a variety of types of medical image. It has been designed to satisfy the following criteria: (a) the software should be portable between different items of hardware with minimal alteration; (b) there should be a simple operator interface to enable use by inexperienced users, while avoiding the need for experienced users to be directed through tedious menu trees; (c) the programming environment should enable simple integration of new data handling protocols. To meet these requirements the software was written in FORTRAN using structured subroutine organization. The software has basic image handling and processing facilities and contains a comprehensive set of nuclear medicine clinical protocols. Other facilities include alignment of images from different modalities with display of superimposed images and ability to handle, analyse and display three-dimensional data sets. Data transfer programs have been written to capture data from gamma camera, CT, MRI, ultrasound and radiographs by converting the images to a common data format. The system provides a hospital with a central digital image handling resource, enabling investigation of the value of digital image processing in potential clinical applications.     

WeAidU-a decision support system for myocardial perfusion images using artificial neural networks

This paper presents a computer-based decision support system for automated interpretation of diagnostic heart images (called WeAidU), which is made available via the Internet. The system is based on image processing techniques, artificial neural networks (ANNs) and large well-validated medical databases. We present results using artificial neural networks, and compare with two other classification methods, on a retrospective data set containing 1320 images from the clinical routine. The performance of the artificial neural networks detecting infarction and ischemia in different parts of the heart, measured as areas under the receiver operating characteristic curves, is in the range 0.83-0.96. These results indicate a high potential for the tool as a clinical decision support system.     

Registration of electronic portal images for patient set-up verification

Images acquired from an electronic portal imaging device are aligned with digitally reconstructed radiographs (DRRs) or other portal images to verify patient positioning during radiation therapy. Most of the currently available computer aided registration methods are based on the manual placement of corresponding landmarks. The purpose of the paper is twofold: (a) the establishment of a methodology for patient set-up verification during radiotherapy based on the registration of electronic portal images, and (b) the evaluation of the proposed methodology in a clinical environment. The estimation of set-up errors, using the proposed methodology, can be accomplished by matching the portal image of the current fraction of the treatment with the portal image of the baseline treatment (reference portal image) using a nearly automated technique. The proposed registration method is tested on a number of phantom data as well as on data from four patients. The phantom data included portal images that corresponded to various positions of the phantom on the treatment couch. For each patient, a set of 30 portal images was used. For the phantom data (for both transverse and lateral portal images), the maximum absolute deviations of the translational shifts were within 1.5 mm, whereas the in-plane rotation angle error was less than 0.5 degrees. The two-way Anova revealed no statistical significant variability both within observer and between-observer measurements (P > 0.05). For the patient data, the mean values obtained with manual and the proposed registration methods were within 0.5 mm. In conclusion, the proposed registration method has been incorporated within a system, called ESTERR-PRO. Its image registration capability achieves high accuracy and both intra- and inter-user reproducibility. The system is fully operational within the Radiotherapy Department of 'HYGEIA' Hospital in Athens and it could be easily installed in any other clinical environment since it requires standardized hardware specifications and minimal human intervention.     

A general software package for the handling of medical images

PICS (portable imaging computer software), is a software system designed for handling and processing a variety of types of medical image. It has been designed to satisfy the following criteria:

(a) the software should be portable between different items of hardware with minimal alteration:

(b) there should be a simple operator interface to enable use by inexperienced users, while avoiding the need for experienced users to be directed through tedious menu trees;

(c) the programming environment should enable simple integration of new data handling protocols.

To meet these requirements the software was written in FORTRAN using structured subroutine organization.

The software has basic image handling and processing facilities and contains a comprehensive set of nuclear medicine clinical protocols. Other facilities include alignment of images from different modalities with display of superimposed images and ability to handle, analyse and display three-dimensional data sets.

Data transfer programs have been written to capture data from gamma camera, CT, AMI, ultrasound and radiographs by converting the images to a common data format.

The system provides a hospital with a central digital image handling resource, enabling investigation of the value of digital image processing in potential clinical applications.     

Progression in diagnostic pathology; development of virtual microscopy and its applications

Many systems have already been designed and successfully used for clinical laboratory and pathological examination. The evolution of image analysis was enabled when analog images of the original glass slides could be transferred to digital images with the rapid development of virtual microscopy and virtual slides depended upon computer technologies. Today, whole slide can be acquired by virtual microscopes. The applications of virtual microscopy and virtual slides for teaching, diagnosis, telepathology, and research are more widely used than those of real microscope and real glass slides. In traditional cancer diagnosis, pathologists examine biopsies to make diagnostic assessments largely based on two-dimensional cell morphology and tissue distribution. These assessments are subjective and often show considerable variability. However, automated cancer diagnostic system based on three-dimensional image analysis based on nuclear bulging sign enables objective judgments using quantitative measurements. We expect that the shortage of pathologists will be improved when an automated cancer diagnosis system is developed.     

Automated Quality Assessment of Colour Fundus Images for Diabetic Retinopathy Screening in Telemedicine

Fundus images obtained in a telemedicine program are acquired at different sites that are captured by people who have varying levels of experience. These result in a relatively high percentage of images which are later marked as unreadable by graders. Unreadable images require a recapture which is time and cost intensive. An automated method that determines the image quality during acquisition is an effective alternative. To determine the image quality during acquisition, we describe here an automated method for the assessment of image quality in the context of diabetic retinopathy. The method explicitly applies machine learning techniques to access the image and to determine ‘accept’ and ‘reject’ categories. ‘Reject’ category image requires a recapture. A deep convolution neural network is trained to grade the images automatically. A large representative set of 7000 colour fundus images was used for the experiment which was obtained from the EyePACS that were made available by the California Healthcare Foundation. Three retinal image analysis experts were employed to categorise these images into ‘accept’ and ‘reject’ classes based on the precise definition of image quality in the context of DR. The network was trained using 3428 images. The method shows an accuracy of 100% to successfully categorise ‘accept’ and ‘reject’ images, which is about 2% higher than the traditional machine learning method. On a clinical trial, the proposed method shows 97% agreement with human grader. The method can be easily incorporated with the fundus image capturing system in the acquisition centre and can guide the photographer whether a recapture is necessary or not.     

Use of a Dedicated Server to Perform Coronal and Sagittal Reformations in Trauma Examinations

The purpose of this study was to evaluate the impact of implementing an automated process for generating coronal and sagittal reformatted images on radiologist workflow. When performing trauma-related CT examinations of the cervical, thoracic, and lumbar spine at our institution, technologists manually generate coronal and sagittal reconstructions at the scanner console and send these images to a picture archiving and communication system (PACS) for interpretation by radiologists and clinical viewing. Although certain PACS, thin-client three-dimensional systems, and CT scanners are capable of automatically generating reconstructed or reformatted images, the systems at our institution do not support this functionality. We have recently integrated a dedicated server that is capable of automatically generating multiplanar reformatted (MPR) images from source thin-section axial images and sending these images to PACS without requiring technologist input. This dedicated server was used to generate coronal and sagittal MPRs for trauma-related spine studies in parallel with technologist-generated coronal and sagittal reconstructions. When comparing the two methods, using the dedicated server to automatically generate reformations resulted in substantial time savings for the radiologist compared to technologist-generated reconstructions. Additionally, a survey of interpreting radiologists indicated that a significant majority preferred to view the automatically generated MPRs on PACS compared to the thin-client system, considered the image quality to be good or excellent, and believed that viewing MPRs increased diagnostic accuracy and confidence. It is expected that this automated process will significantly improve radiologist workflow with respect to image interpretation time and report turnaround time.     

Clinical Utility of Temporal Subtraction Images in Successive Whole-Body Bone Scans: Evaluation in a Prospective Clinical Study

In order to aid radiologists’ routine work for interpreting bone scan images, we developed a computerized method for temporal subtraction (TS) images which can highlight interval changes between successive whole-body bone scans, and we performed a prospective clinical study for evaluating the clinical utility of the TS images. We developed a TS image server which includes an automated image-retrieval system, an automated image-conversion system, an automated TS image-producing system, a computer interface for displaying and evaluating TS images with five subjective scales, and an automated data-archiving system. In this study, the radiologist could revise his/her report after reviewing the TS images if the findings on the TS image were confirmed retrospectively on our clinical picture archiving and communication system. We had 256 consenting patients of whom 143 had two or more whole-body bone scans available for TS images. In total, we obtained TS images successfully in 292 (96.1%) pairs and failed to produce TS images in 12 pairs. Among the 292 TS studies used for diagnosis, TS images were considered as “extremely beneficial” or “somewhat beneficial” in 247 (84.6%) pairs, as “no utility” in 44 pairs, and as “somewhat detrimental” in only one pair. There was no TS image for any pairs that was considered “extremely detrimental.” In addition, the radiologists changed their initial reported impression in 18 pairs (6.2%). The benefit to the radiologist of using TS images in the routine interpretation of successive whole-body bone scans was significant, with negligible detrimental effects.     

A Visual Query-by-Example Image Database for Chest CT Images: Potential Role as a Decision and Educational Support Tool for Radiologists

Primary reading or further evaluation of diagnostic imaging examination often needs a comparison between the actual findings and the relevant prior images of the same patient or similar radiological data found in other patients. This support is of clinical importance and may have significant effects on physicians examination reading efficiency, service-quality, and work satisfaction. We developed a visual query-by-example image database for storing and retrieving chest CT images by means of a visual browser Image Management Environment (IME) and tested its retrieval efficiency. The visual browser IME included four fundamental features (segmentation, indexing, quick load and recall, user-friendly interface) in an integrated graphical environment for a user-friendly image database management. The system was tested on a database of 2000 chest CT images, randomly chosen from the digital archives of our institutions. A sample of eight heterogeneous images were used as queries and, for each of them a team of three expert radiologists selected the most similar images from the database (a set of 15 images containing similar abnormalities in the same position of the query). The sensitivity and the positive predictive factor, both averaged over the 8 test queries and 15 answers, were respectively 0.975 and 0.91 The IME system is currently under evaluation at our institutions as an experimental application. We consider it a useful work-in-progress tool for clinical practice facilitating searches for a variety of radiological tasks.     

Hospital characteristics associated with highly automated and usable clinical information systems in Texas,United States

Background  

A hospital's clinical information system may require a specific environment in which to flourish. This environment is not yet well defined. We examined whether specific hospital characteristics are associated with highly automated and usable clinical information systems.