Journal of Digital Imaging

One can distinguish two distinct preliminary phases in the “analog” radiographs reading process. The first phase deals with the film selection and placement on viewboxes (image organization), and the second with the actual film reading (involving image navigation, ie, the means for accessing the individual images). Our multimedia radiological work station will replace the view boxes with a low-resolution control monitor and a single high-resolution image monitor for viewing the radiographic images of the patient. These are organized by body area and axamination view, and are associated with a sketch of a human body on the control monitor. This “anthropomorphic” organization of the images helps the radiologist create a mental picture of the entire patient radiographic file. We expect that together with the requisition information, a proper representation of the file will improve the search for relevant radiographic images. The work station supports image navigation by means of a “soft” representation of the physical viewboxes. In the same manner that radiographic films can be placed onto physical viewboxes, image labels can be dragged with the mouse onto soft viewboxes embedded on the image monitor. Evaluation of results from tests conducted with 15 physicians are presented.

The need for providers and patients to exchange and share imaging has never been more apparent, yet many organizations are only now, as a part of a larger enterprise imaging initiative, taking steps to streamline an important process that has historically been facilitated with the use of CDs or insecure methods of communication. This paper will provide an introduction to concepts and common-use cases for image exchange, outline challenges that have hindered adoption to date, and describe standards for image exchange that show increasing promise of being adopted by vendors and providers.

In this article we describe a statistical model that was developed to segment brain magnetic resonance images. The statistical segmentation algorithm was applied after a pre-processing stage involving the use of a 3D anisotropic filter along with histogram equalization techniques. The segmentation algorithm makes use of prior knowledge and a probability-based multivariate model designed to semi-automate the process of segmentation. The algorithm was applied to images obtained from the Center for Morphometric Analysis at Massachusetts General Hospital as part of the Internet Brain Segmentation Repository (IBSR). The developed algorithm showed improved accuracy over the k-means, adaptive Maximum Apriori Probability (MAP), biased MAP, and other algorithms. Experimental results showing the segmentation and the results of comparisons with other algorithms are provided. Results are based on an overlap criterion against expertly segmented images from the IBSR. The algorithm produced average results of approximately 80% overlap with the expertly segmented images (compared with 85% for manual segmentation and 55% for other algorithms).

This report summarizes Mayo Clinic Rochester’s experience with a picture archiving and communication system (PACS) to date and discusses the principles that have guided implementation.

Due to the damage to biometric properties in the event of natural disasters, like fire or earthquakes, it is very difficult to identify human remains. As teeth are more durable than other biometric properties, identifying information obtained from them is much more reliable. Therefore, in cases where alternative biometric properties cannot be obtained or used, information taken from teeth may be used to identify a person’s remains. In recent years, many studies have shown how the identification process, previously performed manually by a forensic dental specialist, can be made faster and more reliable with the assistance of computers and technology. In these studies, the x-ray image is subdivided into meaningful parts, including jaws and teeth, and dental properties are extracted and matched. In order to extract the features accurately and ensure better matching, it is important to segment images properly. In this study, (i) lower and upper jaw and (ii) tooth separation was performed to segment panoramic dental x-ray images to assist in identifying human remains. To separate the jaws, a novel meta-heuristic optimization-based model is proposed. To separate teeth, a user-assisted, semi-automatic approach is presented. The proposed methods have been performed with a computer program. The results of the implementation of these methods of jaw and tooth separation in panoramic tooth images are encouraging.

The purpose of this presentation is to review and evaluate computerized workflow of selected sites that have integrated systems of the hospital information system (HIS), radiology information system (RIS), and picture archiving and communications system (PACS). We then focus on some essential points of integration of those systems, such as avoiding multiple entries of patients demographic data, prefetching current and previous images to the correspondent workstations, and workflow management. To realize them by integrating multiple subsystems such as HIS/RIS/PACS integration, there must be exchange of the workflow control information, and consistency of the information between subsystems.