Several DICOM toolkits were selected to be compared for their de-identification capabilities. Similar work examining seven free DICOM software toolkits and their ability to de-identify 38 tags that contain patient or study information using their default and modified configurations has been previously presented. These toolkits offer many features useful for clinical practice or clinical research purposes such as DICOM data validation, image viewing and analysis, PACS server, and converting and modifying, including de-identifying, DICOM data. Various applications, libraries, and frameworks have been developed for handling, viewing, transmitting, and processing DICOM data. This work also provides further consideration of DICOM toolkits that could perform data de-identification to meet regulatory requirements. In this work, ten non-commercial (free) DICOM toolkits were selected and tested for their de-identification effectiveness and completeness to determine the tools’ ability to remove a patient's personal health information (PHI) from the DICOM header. Each tool introduces its own de-identification profiles to remove or replace a selection of header elements and, therefore, produces its own specific outcomes from the data de-identification process. Numerous tools have been built to perform the task of DICOM data de-identification in order to fulfil the requirements of patient data protection. This method is most frequently used in clinical analysis, processing, and research since good clinical practice requires that, should additional findings be encountered that are essential for the well-being of the patient, it should be possible to somehow track the real identity of the patient in order to inform him or her about these findings. The other method, pseudonymization, is implemented by replacing the most identifying fields within a data record using one or more artificial identifiers that could be used by authorized personnel to track down the real identity of the patient. The first method is anonymization which removes information carried by header elements or replaces the information with random data such that the remaining information cannot be used to reveal the patient identity at all. There are two methods to de-identify patient-related information in a DICOM header. Sharing such sensitive data demands proper protection to ensure data safety and maintain patient privacy. These meta-data elements include identifiable information about the patient, the study, and the institution. The tag of an element is written with two hexadecimal numbers indicating its group and element number. Each data element is represented by a unique tag with specific values and data types. DICOM was developed to ease the exchange of data between different manufacturers, but it also enables data sharing between institutions or enterprises for clinical research or clinical practice.Ī DICOM file not only contains a viewable image that holds all of the pixel values but it also contains a header with a large variety of data elements. Because of its structure and open character it can be easily adapted and upgraded to accommodate changes in medical imaging technology. The Digital Imaging and Communication in Medicine (DICOM) standard has been commonly used for storing, viewing, and transmitting information in medical imaging.
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