Deep learning applications in radiology: recent developments, challenges and potential solutions
Radiological Society of North America (RSNA), 103rd Scientific Assembly and Annual Meeting
Abstract
An abstract is not available in the lab archive. View the paper at its source.
This digital education exhibit was listed in the program for RSNA’s 103rd Scientific Assembly and Annual Meeting in 2017. Its presentation materials review deep-learning approaches for medical image analysis, along with challenges, potential solutions and future trends.
Summary
The exhibit reviewed deep-learning approaches to medical image analysis and discussed challenges, potential solutions and future trends. The available abstract describes the work as a review; it does not report a comparative evaluation or clinical validation. View the presentation materials.
Cite this work
Sarfaraz Hussein; Aliasghar Mortazi; Harish Raviprakash; Jeremy R. Burt; Ulas Bagci (2017). Deep learning applications in radiology: recent developments, challenges and potential solutions. Radiological Society of North America (RSNA), 103rd Scientific Assembly and Annual Meeting https://doi.org/10.13140/RG.2.2.11845.96480
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