Stephen T. C. Wong

Radiologic image compression-a review

The objective of radiologic image compression is to reduce the data volume of and to achieve a low bit rate in the digital representation of radiologic images without perceived loss of image quality. However, the demand for transmission bandwidth and storage space in the digital radiology environment, especially picture archiving and communication systems (PACS) and teleradiology, and the proliferating use of various imaging modalities, such as magnetic resonance imaging, computed tomography, ultrasonography, nuclear medicine, computed radiography, and digital subtraction angiography, continue to outstrip the capabilities of existing technologies. The availability of lossy coding techniques for clinical diagnoses further implicates many complex legal and regulatory issues. This paper reviews the recent progress of lossless and lossy radiologic image compression and presents the legal challenges of using lossy compression of medical records. To do so, we first describe the fundamental concepts of radiologic imaging and digitization. Then, we examine current compression technology in the field of medical imaging and discuss important regulatory policies and legal questions facing the use of compression in this field. We conclude with a summary of future challenges and research directions. >

Towards effective and rewarding data sharing.

Recently issued NIH policy statement and implementation guidelines (National Institutes of Health, 2003) promote the sharing of research data. While urging that “all data should be considered for data sharing” and “data should be made as widely and freely available as possible” the current policy requires only high-direct-cost (>US

A hospital integrated framework for multimodality image base management

500,000/yr) grantees to share research data, starting 1 October 2003. Data sharing is central to science, and we agree that data should be made available.

Coping with conflict in cooperative knowledge-based systems

The trend in healthcare information technology is increasingly digital and multimedia oriented. The next generation of health care information systems will consist of a vast network of heterogeneous, autonomous, and distributed imaging scanners, databases, information systems, knowledge intensive applications, and large quantities of multimedia medical data. A key challenge facing system researchers and builders is to provide a new organizational framework that can integrate this varied collection of resources into what appears to be a uniform and logical conglomeration of data and knowledge store in order to increase the availability of global or previously nonaccessible information and to address demanding new information processing requirements for diverse image-assisted medical applications. The purpose of this paper is to present the authors research toward the development of a hospital integrated framework of multimodality image base management (MIBM) for digital radiology of the future. This evolutionary framework consists of three hierarchical components: a hospital-integrated picture archiving and communication system (HI-PACS), a medical image database system (MIDS), and a set of image-based medical applications that relies on the support of MIDS and PACS. In this paper, the authors describe the system architecture, guiding principles, and design specifications of HI-PACS and MIDS and illustrate their functions and capabilities with three implemented applications, namely, patient folder workflow, distributed object management, and multimodality imaging studies. In addition, the authors conclude their findings with a summary of challenges and research directions.

Wavelet-based histogram equalization enhancement of gastric sonogram images

In this paper, we address a critical issue of cooperative problem solving: the existence of conflict among distributed agents. In particular, we focus our study on cooperative knowledge-based systems. To obtain a better understanding and more balanced judgement of multiagent conflict, we provide a general scheme to study the logical structure of multiagent conflict and rational strategies of coping with it under different situations. Our research finding is that there is no grand unified theory of coping with conflict in performing complex real-world computer supported tasks. Instead, a library of alternative methods should be considered. We discuss four methods: inquiry, arbitration, persuasion, and accommodation. These methods can be combined in an order appropriate to the application domain such that if one method fails, the system will try the next. We point out merits and shortcomings of these methods and illustrate them using several high-level protocols and application examples from a prototype system, the Building Design Network.

Networked multimedia for medical imaging

The gray levels of gastric sonogram images are usually concentrated at the zero end of the spectrum, making the image too low in contrast and too dark for the naked eye. Though histogram equalization can enhance the contrast by redistributing the gray levels, it has the drawback that it reduces the information in the processed image. In this paper, a wavelet-based enhancement algorithm post-processor is used to further enhance the image and compensate for the information loss during histogram equalization. Experimental results show that the wavelet-based enhancement algorithm can enhance the contrast and significantly increase the informational entropy of the image. Because the combination of the histogram equalization and wavelet approach can dramatically increase the contrast and maintain information rate in gastric sonograms, it has the potential to improve clinical diagnosis and research.

Multimodal image fusion for noninvasive epilepsy surgery planning

The development of biomedical imaging has revolutionized medical practice and health care delivery. The next wave of change, however, will come from merging medical imaging with multimedia technology. We discuss the necessary information infrastructure and supporting technology for this evolving field. We describe four types of clinical applications to illustrate the use and versatility of networked multimedia systems for image-assisted medical care.

Wavelet-based enhancement for detection of left ventricular myocardial boundaries in magnetic resonance images

A neurodiagnostic workstation integrated into a hospital picture archiving and communication system supports low cost, low risk epilepsy surgery planning by combining biomedical information from four neuroimaging modalities. This medical workstation aims to provide an environment for optimal interpretation of multiple noninvasive image modalities by combining functional PET, MRS, and MEG information with structural MRI anatomy both qualitatively and quantitatively. Since there is currently little knowledge relating to the positive and negative findings of various imaging and intracranial EEG studies on patient populations, the data extracted will also help in outcome analyses to identify inefficient or duplicative evaluation procedures.

COSMO: a communication scheme for cooperative knowledge-based systems

MRI is noninvasive and generates clear images, giving it great potential as a diagnostic instrument. However, current methods of image analysis are too time-consuming for dynamic systems such as the cardiovascular system. Since dynamic imagery generate a huge number of images, a computer aided machine vision diagnostic tool is essential for implementing MRI-based measurement. In this paper, a wavelet-based image technique is applied to enhance left ventricular endocardial and epicardial profiles as the preprocessor for a dynamic programming-based automatic border detection algorithm. Statistical tests are conducted to verify the performance of the enhancement technique by comparing borders manually drawn with 1. borders generated from the enhanced images, and 2. borders generated for the original images.

Temporal image database design for outcome analysis of lung nodule

The purpose of this paper is to present the design principles and features of a communication scheme that has been used to support cooperative problem solving within a network of knowledge-based systems. In presenting this account, we attempt to answer a set of critical yet unsettled questions of cooperative systems communication, such as when and how a knowledge-based system knows what message to send, what the conditions of success are for a message, and how individual systems cooperate with each other for different purposes. To achieve this, we first propose two key design principles: (1) the loose coupling of communication issues and knowledge representation issues, and (2) the notion of communicative acts. We then work these ideas into the communication scheme COSMO, whose key features include knowledge handlers, an operation model, organizational roles, message types, communication strategies, and protocols. >