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01-05-2020 | Transactional Processing Systems

De-Identification of Radiomics Data Retaining Longitudinal Temporal Information

Authors: Surajit Kundu, Santam Chakraborty, Sanjoy Chatterjee, Syamantak Das, Rimpa Basu Achari, Jayanta Mukhopadhyay, Partha Pratim Das, Indranil Mallick, Moses Arunsingh, Tapesh Bhattacharyyaa, Soumendranath Ray

Published in: Journal of Medical Systems | Issue 5/2020

Abstract

We propose a de-identification system which runs in a standalone mode. The system takes care of the de-identification of radiation oncology patient’s clinical and annotated imaging data including RTSTRUCT, RTPLAN, and RTDOSE. The clinical data consists of diagnosis, stages, outcome, and treatment information of the patient. The imaging data could be the diagnostic, therapy planning, and verification images. Archival of the longitudinal radiation oncology verification images like cone beam CT scans along with the initial imaging and clinical data are preserved in the process. During the de-identification, the system keeps the reference of original data identity in encrypted form. These could be useful for the re-identification if necessary.

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Title: De-Identification of Radiomics Data Retaining Longitudinal Temporal Information
Authors: Surajit Kundu
Santam Chakraborty
Sanjoy Chatterjee
Syamantak Das
Rimpa Basu Achari
Jayanta Mukhopadhyay
Partha Pratim Das
Indranil Mallick
Moses Arunsingh
Tapesh Bhattacharyyaa
Soumendranath Ray
Publication date: 01-05-2020
Publisher: Springer US
Published in: Journal of Medical Systems / Issue 5/2020
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-020-01563-0

At a glance: The STEP trials

Springer Medicine

De-Identification of Radiomics Data Retaining Longitudinal Temporal Information

Abstract

At a glance: The STEP trials

Springer Medicine

Abstract

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