Normalizing Heterogeneous Medical Imaging Data to Measure the Impact of Radiation Dose

Abstract

The production of medical imaging is a continuing trend in healthcare institutions. Quality assurance for planned radiation exposure situations (e.g. X-ray, computer tomography) requires examination-specific set-ups according to several parameters, such as patient's age and weight, body region and clinical indication. These data are normally stored in several formats and with different nomenclatures, which hinder the continuous and automatic monitoring of these indicators and the comparison between several institutions and equipment. This article proposes a framework that aggregates, normalizes and provides different views over collected indicators. The developed tool can be used to improve the quality of radiologic procedures and also for benchmarking and auditing purposes. Finally, a case study and several experimental results related to radiation exposure and productivity are presented and discussed.

Dicoogle Open Source: The Establishment of a New Paradigm in Medical Imaging

“…It was also used to index visual features extracted from the pixel data. In the same year, Silva et al [ 48 ] explored the capabilities of Dicoogle to detect and process inconsistencies in radiology departments. The authors focused on the radiation dose, identifying abnormal values, and improving healthcare service quality and safety.…”

“…The authors address problems like dose surveillance and image quality control. Additionally, the authors describe a method to examine and study medical imaging repositories [ 48 ] A Recommender System for Medical Imaging Diagnostic 2015 CBIR, Data mining In this study, the authors used Dicoogle to build a context-based recommender system for diagnostic using medical images. The developed system uses data mining and context-based retrieval mechanisms to automatically identify information relevant to physicians during the diagnostics.…”

Anatomy of an Extensible Open Source PACS

“…By enabling multiple views over the medical data repository in a flexible and efficient way, and with the possibility of exporting data for further statistical analysis, Dicoogle allows identification of inconsistencies in data and processes. This platform can be used to audit PACS information data and contribute to the improvement of radiology department's practices [28,29,33]. Dicoogle has been also extended to support CBIR, using a profile-based approach.…”

“…To do so, we initially relied on the extraction of metadata present in the objects of DICOM repositories and its respective indexation in a Lucene database [13]. This proved a successful approach, validated on the field, where it provided insights efficiency and service quality [28] and on the radiology dosage variation [33]. Our foray into new strategies for information retrieval, such as CBIR, required us to come up with new abstractions that, while allowing us to maintain all previous functionality, are more amenable to extension.…”