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Top Takeaways from SIIM 2020

Top Takeaways from SIIM 2020

Topics related to AI and machine learning in medical imaging continued to be a central point of discussion at SIIM 2020. Read our top takeaways from the virtual meeting.

SIIM 2020 Checkpoint

SIIM 2020 Checkpoint

For many of us in the medical imaging AI field, the annual gathering of the Society for Imaging Informatics in Medicine (SIIM) is one of the most important checkpoints in our year, along with RSNA and other specialty-oriented conferences.

Chest X-Ray and Medical Imaging AI

Chest X-Ray and Medical Imaging AI

As developers of machine learning medical imaging applications, we are often asked: “Why can’t we just have AI read a chest X-ray and classify whether it is normal or not?” How hard could that be? This article explains some of the challenges and what it will take to bring this time-saving innovation into clinical practice.

Selected Publications

NEW Learn to be Uncertain: Leveraging Uncertain Labels in Chest X-rays with Bayesian Neural Networks

Yang HY, Yang J, Pan Y, Cao K, Song Q, et al., Uncertainty and Robustness in Deep Visual Learning Workshop, IEEE Conference on Computer Vision and Pattern Recognition, June, 2019.

NEW Precise Diagnosis of Intracranial Hemorrhage and Subtypes Using a Three-dimensional Joint Convolutional and Recurrent Neural Network

Ye H*, Gao F* (*Equal contribution), Yin Y, Guo D, Zhao P, et al., European Radiology, March, 2019.

NEW DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction

Guo Z, Bai J, Lu Y, Wang X, Cao K, et al., International conference on Information Processing in Medical Imaging (IPMI), 2019.