In October 1993, DICOM (Digital Imaging and Communications in Medicine) Version 3.0 was approved by the ACR-NEMA committee as an ACR-NEMA standard for medical image interchange. At about the same time, IPI (Image Processing and Interchange) was approved as an ISO standard for general imaging. Within the European Committee for Standardisation, CEN, work on a European standard for medical image interchange, MEDICOM, has been going on for the last few years. It has been decided within the CEN Technical Committee for Medical Informatics (CEN/TC 251) that such a European standard should be based on IPI. In December 1993 it was also agreed that CEN would use DICOM 3.0 as a starting point in this work. Joint meetings between CEN/TC 251 Working Group 4 (Medical Imaging and Multimedia) and ACR-NEMA have been held held during 1994 and continue in 1995. This paper points to some of the reasons, both technical and economical, why IPI is suitable for medical imaging. It also shows how DICOM and IPI are complementary and that they could be used together to cover the requirements of future applications in medical imaging.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/BF01143136 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Characterization and Detection Strategy Exploration in Cryptogenic Hepatocellular Carcinoma: Insights From a Super-Aged Region in Japan.
Cancer Med
January 2025
Division of Gastroenterology and Nephrology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan.
Background And Aim: In recent years, there has been a rise in cryptogenic hepatocellular carcinoma (c-HCC) cases in Japan, posing a detection challenge due to an unknown etiology. This study aims to enhance diagnostic strategies for c-HCC by analyzing its characteristics and exploring current opportunities for detection.
Methods: A retrospective study was conducted from April 2012 to March 2022, enrolling 372 newly diagnosed hepatocellular carcinoma (HCC) patients.
Assessing spatial sequencing and imaging approaches to capture the molecular and pathological heterogeneity of archived cancer tissues.
J Pathol
January 2025
The Institute for Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia.
Spatial transcriptomics (ST) offers enormous potential to decipher the biological and pathological heterogeneity in precious archival cancer tissues. Traditionally, these tissues have rarely been used and only examined at a low throughput, most commonly by histopathological staining. ST adds thousands of times as many molecular features to histopathological images, but critical technical issues and limitations require more assessment of how ST performs on fixed archival tissues.
View Article and Find Full Text PDFRecent advances in nanoultrasonography for the diagnosis and treatment of gastrointestinal diseases.
Nanomedicine (Lond)
January 2025
Department of Ultrasound, Yantaishan Hospital, Binzhou Medical University, Yantai, Shandong, China.
With the rapid development of nanotechnology, nanoultrasonography has emerged as a promising medical imaging technique that demonstrates significant potential in the diagnosis and treatment of gastrointestinal (GI) diseases. This review discusses the applications of nanoultrasonography in the gastrointestinal field, including improvements in imaging resolution, diagnostic accuracy, latest research findings, and prospects for clinical application. By analyzing existing literature, we explore the role of nanoultrasonography in enhancing imaging resolution, enabling targeted drug delivery, and improving therapeutic outcomes, thereby providing a reference for future research directions.
View Article and Find Full Text PDFInfarct core segmentation using U-Net in CT perfusion imaging: a feasibility study.
Acta Radiol
January 2025
Department of Medical Imaging, Dalin Tzu-Chi Hospital, Chiayi, Taiwan.
Background: The wide variability in thresholds on computed tomography (CT) perfusion parametric maps has led to controversy in the stroke imaging community about the most accurate measurement of core infarction.
Purpose: To investigate the feasibility of using U-Net to perform infarct core segmentation in CT perfusion imaging.
Material And Methods: CT perfusion parametric maps were the input of U-Net, while the ground truth segmentation was determined based on diffusion-weighted imaging (DWI).
Artificial Intelligence-Based Detection and Numbering of Dental Implants on Panoramic Radiographs.
Clin Implant Dent Relat Res
February 2025
SEMRUK Technology Inc., Cumhuriyet Teknokent, Sivas, Turkiye.
Objectives: This study aimed to develop an artificial intelligence (AI)-based deep learning model for the detection and numbering of dental implants in panoramic radiographs. The novelty of this model lies in its ability to both detect and number implants, offering improvements in clinical decision support for dental implantology.
Materials And Methods: A retrospective dataset of 32 585 panoramic radiographs, collected from patients at Sivas Cumhuriyet University between 2014 and 2024, was utilized.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!