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15 - 19 February 2021
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Digital Breast Tomosynthesis Lesion Detection

Challenge image 2021


Digital Breast Tomosynthesis Lesion Detection Challenge (DBTex)


Overview
We asked for participation in the DBTex Challenge by submitting algorithms for the detection of breast lesions on digital breast tomosynthesis images. The results of the competition were announced at the special session of the SPIE Medical Imaging 2021 conference. Participants in the first DBTex Challenge were encouraged to submit their work for peer review to the SPIE’s Journal of Medical Imaging.

Thank you to our Award Sponsor: Duke Radiology

VIEW THE DBTex CHALLENGE WORKSHOP VIDEO RECORDING

Read further details within SPIE Technical Events

Read the SPIE Press Release 


 
Key dates for the DBTex Challenge:

Release date of training set cases with truth 14 December
Release date of validation set cases 4 January 2021
Release date of test set cases 15 January 2021
Submission date for participants’ test set output 25 January 2021
Challenge results released to participants 4 February 2021
SPIE Medical Imaging Digital Forum 15-19 February
Challenge results shared LIVE 1:00 - 2:20 PM (PST) Add to calendar 16 February



 
Challenge Proposal


Researchers can participate in the DBTex Challenge by submitting results from their algorithms for the detection of biopsy-proven breast lesions on digital breast tomosynthesis (DBT) images. The DBTex Challenge will provide a unique opportunity for participants to compare their breast lesion detection algorithms with those of others from academia, industry, and government in a structured, direct way using a large set of DBT images. The results of the competition will be showcased at a special session of the Computer-Aided Diagnosis (CAD) conference, part of the SPIE Medical Imaging 2021 Digital Forum. In addition, participants in the DBTex Challenge are encouraged to submit their work for peer review to the SPIE’s Journal of Medical Imaging.



The winning team will receive a $1,000 prize sponsored by DAIR, contingent on making their code publicly available on GitHub. Depositing of code is only required in order to be eligible to win the prize, but all participants are encouraged to make their code publicly available. Additionally, two individuals from each of the two top-performing teams as well as one individual from the third best-performing team will receive a waiver of the SPIE Medical Imaging Symposium in order to present their methods during the meeting.



The Challenge is the 4th such challenge led by SPIE, AAPM, and NCI – the first to include a collaboration with DAIR – and to be showcased at SPIE Medical Imaging, following 2015's LUNGx Challenge, which tasked participants to classify lung nodules on diagnostic computed tomography (CT) scans as benign or malignant; the two-part PROSTATEx Challenge in 2017, which focused on the development of quantitative image-analysis methods for the diagnostic classification of clinically significant prostate lesions and quantitative MRI biomarkers used to determine Gleason Grade Group in prostate cancers; and 2018’s BreastPathQ Cancer Cellularity Challenge which focused on developing and accessing cancer cellularity, a quantitative estimation task in digital pathology.


For more information, access to the training data, and to participate in the DBTex Challenge please visit the Challenge webpage





Organizers:

This challenge is organized by SPIE, the international society for optics and photonics, in conjunction with the American Association of Physicists in Medicine (AAPM), the National Cancer Institute (NCI), and the Duke Center for Artificial Intelligence in Radiology (DAIR), is organizing the Digital Breast Tomosynthesis Lesion Detection Challenge (DBTex). 

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