Cancer Imaging Archive Updates: December 2020

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

TCIA Update: December 2020

The Fredrick National Lab is seeking proposals to label TCIA datasets to make them more readily usable by data scientists for  Artificial Intelligence and other quantitative imaging analyses. More information about this solicita­tion can be found at : https://frederick.cancer.gov/workwithus/solicitations/ s21-112f

TCIA has published the 1st of 3 datasets we're curating from the RSNA "RICORD" project. It consists of 120 thoracic computed tomography (CT) scans from 4 international sites annotated with detailed segmentation and diagnostic labels. Download it here! https://doi.org/10.7937/VTW4-X588

NEW MACHINE LEARNING CHALLENGE!  SPIE and AAPM  launched a new challenge to develop algorithms for breast lesion detection in digital breast tomosynthesis images. This challenge is being conducted using the recently released "Breast Cancer Screening – Digital Breast Tomosynthesis (BCS-DBT)" collection on TCIA!  Find the challenge website here.

Earlier this year, NCI’s Patient-Derived Models Repository & The Cancer   Imaging Archive released spontaneous metastatic PDX models to the public with the accompanying imaging characterization: https://buff.ly/3gBq4gw  A great research resource and  NCI Highlight of 2020.

Over 1,000 publications have been written about TCIA datasets. Watch the RSNA 2020 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

Interested in learning more about using TCIA for AI applications? Watch the RSNA 2020 Featured Session "Creating Publicly Accessible Radiology Imag­ing Resources for Machine Learning and AI"! More details at https://rsna2020.rsna.org/sessions.

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