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Article

ePAD: An Image Annotation and Analysis Platform for Quantitative Imaging

by
Daniel L. Rubin
*,
Mete Ugur Akdogan
,
Cavit Altindag
and
Emel Alkim
Department of Biomedical Data Science, Radiology, and Medicine (Biomedical Informatics Research), Medical School Office Building (MSOB) 1265 Welch Road, X335 Stanford, Stanford University, Stanford, CA 94305-5464, USA
*
Author to whom correspondence should be addressed.
Tomography 2019, 5(1), 170-183; https://doi.org/10.18383/j.tom.2018.00055
Submission received: 8 December 2018 / Revised: 1 January 2019 / Accepted: 7 February 2019 / Published: 1 March 2019

Abstract

Medical imaging is critical for assessing the response of patients to new cancer therapies. Quantitative lesion assessment on images is time-consuming, and adopting new promising quantitative imaging biomarkers of response in clinical trials is challenging. The electronic Physician Annotation Device (ePAD) is a freely available web-based zero-footprint software application for viewing, annotation, and quantitative analysis of radiology images designed to meet the challenges of quantitative evaluation of cancer lesions. For imaging researchers, ePAD calculates a variety of quantitative imaging biomarkers that they can analyze and compare in ePAD to identify potential candidates as surrogate endpoints in clinical trials. For clinicians, ePAD provides clinical decision support tools for evaluating cancer response through reports summarizing changes in tumor burden based on different imaging biomarkers. As a workflow management and study oversight tool, ePAD lets clinical trial project administrators create worklists for users and oversee the progress of annotations created by research groups. To support interoperability of image annotations, ePAD writes all image annotations and results of quantitative imaging analyses in standardized file formats, and it supports migration of annotations from various propriety formats. ePAD also provides a plugin architecture supporting MATLAB server-side modules in addition to client-side plugins, permitting the community to extend the ePAD platform in various ways for new cancer use cases. We present an overview of ePAD as a platform for medical image annotation and quantitative analysis. We also discuss use cases and collaborations with different groups in the Quantitative Imaging Network and future directions.
Keywords: medical image annotation; biomarker evaluation; feature extraction; AIM (Annotation and Image Markup); DICOM SR (DICOM Structure Report) medical image annotation; biomarker evaluation; feature extraction; AIM (Annotation and Image Markup); DICOM SR (DICOM Structure Report)

Share and Cite

MDPI and ACS Style

Rubin, D.L.; Akdogan, M.U.; Altindag, C.; Alkim, E. ePAD: An Image Annotation and Analysis Platform for Quantitative Imaging. Tomography 2019, 5, 170-183. https://doi.org/10.18383/j.tom.2018.00055

AMA Style

Rubin DL, Akdogan MU, Altindag C, Alkim E. ePAD: An Image Annotation and Analysis Platform for Quantitative Imaging. Tomography. 2019; 5(1):170-183. https://doi.org/10.18383/j.tom.2018.00055

Chicago/Turabian Style

Rubin, Daniel L., Mete Ugur Akdogan, Cavit Altindag, and Emel Alkim. 2019. "ePAD: An Image Annotation and Analysis Platform for Quantitative Imaging" Tomography 5, no. 1: 170-183. https://doi.org/10.18383/j.tom.2018.00055

APA Style

Rubin, D. L., Akdogan, M. U., Altindag, C., & Alkim, E. (2019). ePAD: An Image Annotation and Analysis Platform for Quantitative Imaging. Tomography, 5(1), 170-183. https://doi.org/10.18383/j.tom.2018.00055

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