Yearly Archives: 2017
12 DecRSNA 2017 Summary: AI all the rage, access to annotated data a challenge
There is a nice description of AI in medical imaging from Signify Research that concludes, “Access to radiologist annotated data remains a major challenge for many algorithm developers, who must be prepared to invest significant time and money in data curation. Companies with innovative strategies for obtaining data will have a big advantage.” Hey, that’s what we […]
Read More ...15 NovSfN 2017 Poster
Using a probabilistic atlas to improve manual parcellation of the cerebellum Andrew Worth1, Jason Tourville2 1 Neuromorphometrics, Inc., Somerville, MA 2 Dept. of Speech, Language, and Hearing Sciences, Boston University, Boston, MA Abstract (download poster, 6.1MB) In order to develop automated methods for labeling anatomy in MRI brain scans, regions of interest (ROIs) must first be labeled manually and […]
Read More ...15 JunDeep learning needs [expert] data!
“DeepMind Shows AI Has Trouble Seeing Homer Simpson’s Actions” (link), describes how machine learning (deep learning, neural networks, artificial intelligence) needs annotated data to train on so they went with Amazon’s Mechanical Turk service to create it. That works because we all have visual systems that to a great job. But some deep learning applications need expertise beyond what […]
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