Cancer Imaging Archive Updates: November 2020

[Tacconelli, Michelle (NIH/NCI) [C]]

TCIA Update: November 2020

Over 1,000 publications have been written about TCIA datasets. Join us   December 1st at 2pm Central for our #RSNA20 session "Novel Discoveries Using the NCI's Cancer Imaging Archive Public Data Sets" to hear some of the recent highlights! https://rsna2020.rsna.org/sessions

Attending RSNA 2020? Watch the Featured Session "Creating Publicly Ac­cessible Radiology Imaging Resources for Machine Learning and AI"! More details at https://rsna2020.rsna.org/sessions.

The QIN-Prostate-Repeatability collection (previously limited-access) is now publicly available! It contains multiparametric prostate MRI applied in a test-retest setting, allowing to evaluate repeatability of the MRI-based measure­ments. http://doi.org/10.7937/K9/TCIA.2018.MR1CKGND

TCIA recently deployed IBM Aspera to facilitate high-speed downloads of digitized pathology data from our CPTAC and NLST collections. We'll be continuing to add Aspera download options for other big datasets soon! Con­tact the TCIA Helpdesk if you have any trouble using it!

"High Resolution Prostate Segmentations for the ProstateX-Challenge"     analyzed 66 T2 MRI scans from the competition to provide ground truth for training CNNs, and to improve the segmentation accuracy of automated al­gorithms: https://doi.org/10.7937/TCIA.2019.DEG7ZG1U.

A new Analysis Result dataset derived from the Ivy GAP collection is now available at https://doi.org/10.7937/9j41-7d44. It includes expert segmenta­tion labels (NIfTI format) for tumor sub-compartments of the pre-operative scans and robust radiomic features (xlsx/csv format).

The MICCAI-endorsed "COVID-19 Lung CT Lesion Segmentation Chal­lenge" is leveraging TCIA data! The competition starts November 2. Find more information about the challenge here.

Check out our 1st ultrasound collection, Prostate-MRI-US-Biopsy! The 1,151 patient dataset was derived from tracked biopsy sessions using the Artemis biopsy system, many of which included image fusion with MRI targets which can be visualized in 3D Slicer: https://doi.org/10.7937/TCIA.2020.A61IOC1A

We've broken 1,000 publications based on TCIA datasets! Congratulations to all of you who have contributed these data or written papers about them. We can't wait to see what discoveries your future work will bring thanks to data sharing in the cancer imaging community.

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