- Created by Tracy Nolan, last modified by Quasar Jarosz on Jun 03, 2020
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Summary
Data was generated as part of two ongoing clinical trials investigating the use of contrast-enhanced ultrasound to a) characterize indeterminate liver lesions and b) monitor treatment response to loco regional therapy. Ultrasound data was obtained on a variety of state of the art ultrasound scanners with curvilinear probes. Gain, dynamic range, focus position and depth were optimized for image quality by the performing sonographer. Images of the mass in both sagittal and transverse planes were obtained and saved in DICOM format. The reference standard used for lesion characterization included tissue pathology and contrast-enhanced cross-sectional imaging within 1 month of the ultrasound exam.
We expect these images can be used in a wide variety of image processing application. We are currently exploring a variety of automated intelligence algorithms for AI-based lesion characterization. Algorithms for object detection and segmentation may also be of interest. As the studies that have generated this data are also ongoing, it is expected that we can add volumetric data, contrast-enhanced ultrasound cine loops, and longer-term treatment response data to this data set in the future.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
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Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.
- Continue with any names from additional submitting sites if collection consists of more that one.
- This work was supported in whole or in part under R01 CA194307 ; R01 CA215520 .
Data Access
Click the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever . Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.
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Clinical Data (xlsx or JSON) |
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Click the Versions tab for more info about data releases.
Detailed Description
Image Statistics |
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Modalities |
US (B-Mode) |
Number of Participants |
200 |
Number of Studies |
400 |
Number of Series |
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Number of Images |
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Images Size (GB) |
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Add any additional information as needed below. Likely would be something from site.
Citations & Data Usage Policy
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Users of this data must abide by the TCIA Data Usage Policy and the Creative Commons Attribution 3.0 Unported License under which it has been published. Attribution should include references to the following citations:
Data Citation
DOI goes here. Create using pubhub with information from Collection Approval form
Acknowledgement
<coming soon>
TCIA Citation
Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7
Other Publications Using This Data
TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.
Version X (Current): Updated yyyy/mm/dd
Data Type | Download all or Query/Filter |
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Images (DICOM, xx.x GB) |
(Requires NBIA Data Retriever .) |
Clinical Data (CSV) | Link |
Other (format) |
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Added new subjects.
Version 1: Updated 2018/10/24
Added new subjects.
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