DICOM

About: DICOM is a research topic. Over the lifetime, 3375 publications have been published within this topic receiving 35658 citations. The topic is also known as: Digital Imaging and Communications in Medicine.

Digital Imaging and Communications in Medicine (DICOM): A Practical Introduction and Survival Guide

Abstract: O.S. Pianykh Berlin, Germany: Springer-Verlag, 2008, 383 pages, $119 The goals of DICOM are to achieve compatibility and improve workflow efficiency between imaging systems and other information systems in health care. Every major vendor of diagnostic medical imaging in the world has incorporated

Preparing a collection of radiology examinations for distribution and retrieval

Abstract: Objective Clinical documents made available for secondary use play an increasingly important role in discovery of clinical knowledge, development of research methods, and education. An important step in facilitating secondary use of clinical document collections is easy access to descriptions and samples that represent the content of the collections. This paper presents an approach to developing a collection of radiology examinations, including both the images and radiologist narrative reports, and making them publicly available in a searchable database. Materials and Methods The authors collected 3996 radiology reports from the Indiana Network for Patient Care and 8121 associated images from the hospitals’ picture archiving systems. The images and reports were de-identified automatically and then the automatic de-identification was manually verified. The authors coded the key findings of the reports and empirically assessed the benefits of manual coding on retrieval. Results The automatic de-identification of the narrative was aggressive and achieved 100% precision at the cost of rendering a few findings uninterpretable. Automatic de-identification of images was not quite as perfect. Images for two of 3996 patients (0.05%) showed protected health information. Manual encoding of findings improved retrieval precision. Conclusion Stringent de-identification methods can remove all identifiers from text radiology reports. DICOM de-identification of images does not remove all identifying information and needs special attention to images scanned from film. Adding manual coding to the radiologist narrative reports significantly improved relevancy of the retrieved clinical documents. The de-identified Indiana chest X-ray collection is available for searching and downloading from the National Library of Medicine ( ).

Medical Image File Formats

Abstract: Image file format is often a confusing aspect for someone wishing to process medical images. This article presents a demystifying overview of the major file formats currently used in medical imaging: Analyze, Neuroimaging Informatics Technology Initiative (Nifti), Minc, and Digital Imaging and Communications in Medicine (Dicom). Concepts common to all file formats, such as pixel depth, photometric interpretation, metadata, and pixel data, are first presented. Then, the characteristics and strengths of the various formats are discussed. The review concludes with some predictive considerations about the future trends in medical image file formats.

Authenticity and integrity of digital mammography images

Abstract: Data security becomes more and more important in telemammography which uses a public high-speed wide area network connecting the examination site with the mammography expert center. Generally, security is characterized in terms of privacy, authenticity and integrity of digital data. Privacy is a network access issue and is not considered in this paper. The authors present a method, authenticity and integrity of digital mammography, here which can meet the requirements of authenticity and integrity for mammography image (IM) transmission. The authenticity and integrity for mammography (AIDM) consists of the following four modules. (1) Image preprocessing: To segment breast pixels from background and extract patient information from digital imaging and communication in medicine (DICOM) image header. (2) Image hashing: To compute an image hash value of the mammogram using the MD5 hash algorithm. (3) Data encryption: To produce a digital envelope containing the encrypted image hash value (digital signature) and corresponding patient information. (4) Data embedding: To embed the digital envelope into the image. This is done by replacing the least significant bit of a random pixel of the mammogram by one bit of the digital envelope bit stream and repeating for all bits in the bit stream. Experiments with digital IMs demonstrate the following. (1) In the expert center, only the user who knows the private key ran open the digital envelope and read the patient information data and the digital signature of the mammogram transmitted from the examination site. (2) Data integrity can he verified by matching the image hash value decrypted from the digital signature with that computed from the transmitted image. (3) No visual quality degradation is detected in the embedded image compared with the original. The authors' preliminary results demonstrate that AIDM is an effective method for image authenticity and integrity in telemammography application.