B-mode ultrasound data of a variety of liver masses (B-mode-and-CEUS-Liver)

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:

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.
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This work was supported in whole or in part under R01 CA194307 ; R01 CA215520 .

Data Access

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Detailed Description

Image Statistics
Modalities	US (B-Mode)
Number of Participants	200
Number of Studies	400
Number of Series
Number of Images
Images Size (GB)

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Acknowledgement

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

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Version 1: Updated 2018/10/24