Rita Noumeir

Methods for image authentication: a survey

Image authentication techniques have recently gained great attention due to its importance for a large number of multimedia applications. Digital images are increasingly transmitted over non-secure channels such as the Internet. Therefore, military, medical and quality control images must be protected against attempts to manipulate them; such manipulations could tamper the decisions based on these images. To protect the authenticity of multimedia images, several approaches have been proposed. These approaches include conventional cryptography, fragile and semi-fragile watermarking and digital signatures that are based on the image content. The aim of this paper is to present a survey and a comparison of emerging techniques for image authentication. Methods are classified according to the service they provide, that is strict or selective authentication, tamper detection, localization and reconstruction capabilities and robustness against different desired image processing operations. Furthermore, we introduce the concept of image content and discuss the most important requirements for an effective image authentication system design. Different algorithms are described and we focus on their comparison according to the properties cited above.

Benefits of the DICOM Structured Report

Recently, the digital imaging and communications in medicine (DICOM) standard introduced rules for the encoding, transmission, and storage of the imaging diagnostic report. This medical document can be stored and communicated with the images in picture archiving and communication system (PACS). It is a structured document that contains text with links to other data such as images, waveforms, and spatial or temporal coordinates. Its structure, along with its wide use of coded information, enables the semantic understanding of the data that is essential for the Electronic Healthcare Record deployment. In this article, we present DICOM Structured Report (SR) and discuss its benefits. We show how SR enables efficient radiology workflow, improves patient care, optimizes reimbursement, and enhances the radiology ergonomic working conditions. As structured input significantly alters the interpretation process, understanding all its benefits is necessary to support the change.

Pseudonymization of radiology data for research purposes.

Medical image processing methods and algorithms, developed by researchers, need to be validated and tested. Test data would ideally be real clinical data especially that clinical data is varied and exists in large volumes. Nowadays, clinical data is accessible electronically and has important value for researchers. However, the usage of clinical data for research purposes should respect data confidentiality, patient right to privacy, and patient consent. In fact, clinical data is nominative given that it contains information about the patient such as name, age, and identification number. Evidently, clinical data needs to be de-identified to be exported to research databases. However, the same patient is usually followed during a long period of time. The disease progression and the diagnostic evolution represent extremely valuable information for researchers as well. Our objective is to build a research database from de-identified clinical data while enabling the data set to be easily incremented by exporting new pseudonymous data, acquired over a long period of time. Pseudonymization is data de-identification, such that data belonging to an individual in the clinical environment still belong to the same individual in the de-identified research version. In this paper, we explore various software architectures to enable the implementation of an imaging research database that can be incremented in time. We also evaluate their security and discuss their security pitfalls. As most imaging data accessible electronically is available with the digital imaging and communication in medicine (DICOM) standard, we propose a de-identification scheme that closely follows DICOM recommendations. Our work can be used to enable electronic health record (EHR) secondary usage such as public surveillance and research, while maintaining patient confidentiality.

DICOM structured report document type definition

The digital imaging and communications in medicine (DICOM) standard recently introduced rules for the encoding, transmission and storage of the structured diagnostic report. This medical document can be stored and communicated with the images. It has a structure and may contain text, with links to other data such as images, waveforms and spatial or temporal coordinates. The prompt availability of the radiology report is crucial for implementing a patient electronic record. Using the extensible markup language (XML) to encode the radiology report broadens its accessibly. This paper presents a document type definition (DTD) that accurately models the DICOM structured report content, structure, and constraints.

Benefits of the DICOM Modality Performed Procedure Step

A few years ago, the Digital Imaging and Communications in Medicine standard introduced a network transaction that is initiated by modality equipment, mainly at the beginning and at the end of the acquisition. This transaction, the Modality Performed Procedure Step (MPPS), is sent to the Picture Archiving and Communication System and/or to the Radiology Information System. It carries information about what really has been performed by the modality equipment during acquisition. In this paper, we present MPPS and discuss its benefits. We show how MPPS enables efficient radiology workflow and how it ensures accuracy and completeness of imaging information. We think our paper helps bridge the gap between MPPS implementation and deployment. By understanding all the MPPS benefits, the end user becomes aware of the great enhancement in patient care that this transaction provides.

IHE cross-enterprise document sharing for imaging: interoperability testing software

BackgroundWith the deployments of Electronic Health Records (EHR), interoperability testing in healthcare is becoming crucial. EHR enables access to prior diagnostic information in order to assist in health decisions. It is a virtual system that results from the cooperation of several heterogeneous distributed systems. Interoperability between peers is therefore essential. Achieving interoperability requires various types of testing. Implementations need to be tested using software that simulates communication partners, and that provides test data and test plans.ResultsIn this paper we describe a software that is used to test systems that are involved in sharing medical images within the EHR. Our software is used as part of the Integrating the Healthcare Enterprise (IHE) testing process to test the Cross Enterprise Document Sharing for imaging (XDS-I) integration profile. We describe its architecture and functionalities; we also expose the challenges encountered and discuss the elected design solutions.ConclusionsEHR is being deployed in several countries. The EHR infrastructure will be continuously evolving to embrace advances in the information technology domain. Our software is built on a web framework to allow for an easy evolution with web technology. The testing software is publicly available; it can be used by system implementers to test their implementations. It can also be used by site integrators to verify and test the interoperability of systems, or by developers to understand specifications ambiguities, or to resolve implementations difficulties.

Images within the Electronic Health Record

Cross-Enterprise Document Sharing for Imaging (XDS-I) lays the basic framework for deploying medical images in the Electronic Health Record (EHR). During deployment efforts in many countries, a main challenge has arisen from the need to compare old images with current ones. Presently, most medical imaging applications are part of a broader system known as Picture Archiving and Communication System (PACS); they visualize and process images that they manage and archive; they need to import images for visualization which leads to a problem related to persistency management and information consistency. A solution consisting in avoiding image import is achievable with image streaming. In this paper we describe how XDS-I can be used in conjunction with Web Access to DICOM Persistent Objects (WADO) and DICOM transfer syntax for JPEG 2000 Interactive Protocol (JPIP) to enable streaming of medical images directly from EHR connected imaging sources to image processing workstations.

Integrating the healthcare enterprise process

Integrating the healthcare enterprise (IHE) is an initiative where healthcare professionals and industry providers work together to improve the way healthcare computer systems share information and achieve a high level of interoperability. With IHE, the care providers identify the needs for integration, and manufacturers implement solutions, providing systems that communicate better, are easier to deploy and less expensive to maintain. Successfully implemented in such clinical domains as radiology, laboratory services and cardiology, IHE is expanding into new domains, such as ophthalmology and medical devices, and solving integration problems common to all clinical domains, including patient management, order management, registry, security and document sharing. In this paper, we describe and analyse the collaborative and rigorous IHE process that delivers faster, more efficient and cost-effective systems integration and show how IHE can help healthcare policymakers, executives, and professionals to achieve optimal patient care.

Sharing Medical Records: The XDS Architecture and Communication Infrastructure

Learn how the Cross-Enterprise Document Sharing (XDS) integration profile helped provide the interoperability necessary to deploy electronic health records, giving healthcare providers access to medical records regardless of location or institution.

Attenuation correction in SPECT using active surfaces

To compensate for the photon attenuation in SPECT, we propose to determine the boundary of the uniform attenuation map by detecting the surface of the patient body from the emission data. We use an active surface model which is a three dimensional generalisation of the active contour model known as snakes. The model is an elastic surface that is deformed under the action of internal and external forces. The internal forces model the smoothness constraints while the external forces model the image constraints. In our case, the image constraints are three-dimensional detected edges obtained using the Zucker and Hummel operator applied on the emission volume. The finite difference method is used to solve the energy-minimisation problem for a surface. The segmentation of the patient body from the emission tomography reconstruction is compared to the segmentation from the transmission tomography reconstruction. Moreover, tomography reconstruction corrected for the non-uniform attenuation is compared to the tomography reconstruction corrected for the uniform attenuation. Uniform attenuation correction is performed using the boundary detected from the emission data.