David A. Clunie

Bio: David A. Clunie is an academic researcher from Princeton University. The author has contributed to research in topics: DICOM & Interoperability. The author has an hindex of 18, co-authored 47 publications receiving 1241 citations. Previous affiliations of David A. Clunie include Core Laboratories & Quintiles.

Lossless compression of grayscale medical images : Effectiveness of traditional and state of the art approaches

Abstract: Proprietary compression schemes have a cost and risk associated with their support, end of life and interoperability. Standards reduce this cost and risk. The new JPEG-LS process (ISO/IEC 14495-1), and the lossless mode of the proposed JPEG 2000 scheme (ISO/IEC CD15444-1), new standard schemes that may be incorporated into DICOM, are evaluated here. Three thousand, six hundred and seventy-nine (3,679) single frame grayscale images from multiple anatomical regions, modalities and vendors, were tested. For all images combined JPEG-LS and JPEG 2000 performed equally well (3.81), almost as well as CALIC (3.91), a complex predictive scheme used only as a benchmark. Both out-performed existing JPEG (3.04 with optimum predictor choice per image, 2.79 for previous pixel prediction as most commonly used in DICOM). Text dictionary schemes performed poorly (gzip 2.38), as did image dictionary schemes without statistical modeling (PNG 2.76). Proprietary transform based schemes did not perform as well as JPEG-LS or JPEG 2000 (S+P Arithmetic 3.4, CREW 3.56). Stratified by modality, JPEG-LS compressed CT images (4.00), MR (3.59), NM (5.98), US (3.4), IO (2.66), CR (3.64), DX (2.43), and MG (2.62). CALIC always achieved the highest compression except for one modality for which JPEG-LS did better (MG digital vendor A JPEG-LS 4.02, CALIC 4.01). JPEG-LS outperformed existing JPEG for all modalities. The use of standard schemes can achieve state of the art performance, regardless of modality, JPEG-LS is simple, easy to implement, consumes less memory, and is faster than JPEG 2000, though JPEG 2000 will offer lossy and progressive transmission. It is recommended that DICOM add transfer syntaxes for both JPEG-LS and JPEG 2000.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

ACR–AAPM–SIIM Technical Standard for Electronic Practice of Medical Imaging

Abstract: This technical standard has been revised by the American College of Radiology (ACR), the American Association of Physicists in Medicine (AAPM), and the Society for Imaging Informatics in Medicine (SIIM). For the purpose of this technical standard, the images referred to are those that diagnostic radiologists would normally interpret, including transmission projection and cross-sectional X-ray images, ionizing radiation emission images, and images from ultrasound and magnetic resonance modalities. Research, nonhuman and visible light images (such as dermatologic, histopathologic, or endoscopic images) are out of scope, though many of the same principles are applicable. Increasingly, medical imaging and patient information are being managed using digital data during acquisition, transmission, storage, display, interpretation, and consultation. The management of these data during each of these operations may have an impact on the quality of patient care. This technical standard is applicable to any system of digital image data management, from a single-modality or single-use system to a complete picture archiving and communication system (PACS) to the electronic transmission of patient medical images from one location to another for the purposes of interpretation and/or consultation. It defines goals, qualifications of personnel, equipment guidelines, specifications of data manipulation and management, and quality control and quality improvement procedures for the use of digital image data that should result in high-quality radiological care. A glossary of commonly used terminology (Appendix A) and a reference list are included. In all cases for which an ACR practice guideline or technical standard exists for the modality being used or the specific examination being performed, that practice guideline or technical standard will continue to apply when digital image data management systems are used. Digital mammography is outside the scope of this document. For further information, see the ACR–AAPM–SIIM Practice Guideline for Determinants of Image Quality in Digital Mammography. The goals of the electronic practice of medical imaging include, but are not limited to: Initial acquisition or generation and recording of accurately labeled and identified image data. Transmission of data to an appropriate storage medium from which it can be retrieved for display for formal interpretation, review, and consultation. Retrieval of data from available prior imaging studies to be displayed for comparison with a current study. Transmission of data to remote sites for consultation, review, or formal interpretation. Appropriate compression of image data to facilitate transmission or storage, without loss of clinically significant information. Archiving of data to maintain accurate patient medical records in a form that: May be retrieved in a timely fashion Meets applicable facility, state, and federal regulations Maintains patient confidentiality Promoting efficiency and quality improvement. Providing interpreted images to referring providers. Supporting telemedicine by making medical image consultations available in medical facilities without on-site medical imaging support. Providing supervision of off-site imaging studies. Providing timely availability of medical images, image consultation, and image interpretation by: Facilitating medical image interpretations in on-call situations Providing subspecialty support as needed. Enhancing educational opportunities for practicing radiologists. Minimizing the occurrence of poor image quality. Appropriate database management procedures applicable to all of the above should be in place.

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

Abstract: Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM(®)) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.

Consistency and Standardization of Color in Medical Imaging: a Consensus Report

Abstract: This article summarizes the consensus reached at the Summit on Color in Medical Imaging held at the Food and Drug Administration (FDA) on May 8–9, 2013, co-sponsored by the FDA and ICC (International Color Consortium). The purpose of the meeting was to gather information on how color is currently handled by medical imaging systems to identify areas where there is a need for improvement, to define objective requirements, and to facilitate consensus development of best practices. Participants were asked to identify areas of concern and unmet needs. This summary documents the topics that were discussed at the meeting and recommendations that were made by the participants. Key areas identified where improvements in color would provide immediate tangible benefits were those of digital microscopy, telemedicine, medical photography (particularly ophthalmic and dental photography), and display calibration. Work in these and other related areas has been started within several professional groups, including the creation of the ICC Medical Imaging Working Group.

반도체 공정 overview

Abstract: With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.

The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS

Abstract: LOCO-I (LOw COmplexity LOssless COmpression for Images) is the algorithm at the core of the new ISO/ITU standard for lossless and near-lossless compression of continuous-tone images, JPEG-LS. It is conceived as a "low complexity projection" of the universal context modeling paradigm, matching its modeling unit to a simple coding unit. By combining simplicity with the compression potential of context models, the algorithm "enjoys the best of both worlds." It is based on a simple fixed context model, which approaches the capability of the more complex universal techniques for capturing high-order dependencies. The model is tuned for efficient performance in conjunction with an extended family of Golomb (1966) type codes, which are adaptively chosen, and an embedded alphabet extension for coding of low-entropy image regions. LOCO-I attains compression ratios similar or superior to those obtained with state-of-the-art schemes based on arithmetic coding. Moreover, it is within a few percentage points of the best available compression ratios, at a much lower complexity level. We discuss the principles underlying the design of LOCO-I, and its standardization into JPEC-LS.

Blood–brain barrier leakage may lead to progression of temporal lobe epilepsy

Abstract: Leakage of the blood-brain barrier (BBB) is associated with various neurological disorders, including temporal lobe epilepsy (TLE). However, it is not known whether alterations of the BBB occur during epileptogenesis and whether this can affect progression of epilepsy. We used both human and rat epileptic brain tissue and determined BBB permeability using various tracers and albumin immunocytochemistry. In addition, we studied the possible consequences of BBB opening in the rat for the subsequent progression of TLE. Albumin extravasation in human was prominent after status epilepticus (SE) in astrocytes and neurons, and also in hippocampus of TLE patients. Similarly, albumin and tracers were found in microglia, astrocytes and neurons of the rat. The BBB was permeable in rat limbic brain regions shortly after SE, but also in the latent and chronic epileptic phase. BBB permeability was positively correlated to seizure frequency in chronic epileptic rats. Artificial opening of the BBB by mannitol in the chronic epileptic phase induced a persistent increase in the number of seizures in the majority of rats. These findings indicate that BBB leakage occurs during epileptogenesis and the chronic epileptic phase and suggest that this can contribute to the progression of epilepsy.