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| Content Provider | ACM Digital Library |
|---|---|
| Author | Roos, Justus Rubin, Geoffrey D. Paik, David Napel, Sandy Schmitzberger, Florian F. |
| Abstract | We implemented a system for remote radiology learning which provides immediate feedback to the learner. Using a thin remote client, expert readers are asked to answer questions about specified radiological findings. These scans are presented as realtime 2D and 3D presentations which allow the user to freely manipulate them using a thin Java client with all 3D rendering performed on the server side. Answers are stored on the server and are used to provide feedback to learners who are presented with the same questions, using the remote client. Learners can practice on real datasets while receiving immediate feedback on their diagnosis and measurements. Novel concepts introduced are (1) the use of server-side rendering in radiology learning, (2) providing immediate and specific feedback to trainees, (3) the ability to provide useful feedback when a definitive gold standard does not exist and (4) a thin, highly compatible client that runs on common, existing hardware which allows to have more people participating in very complex radiological evaluations, even if there are not at the same site. |
| Starting Page | 842 |
| Ending Page | 846 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781605581668 |
| DOI | 10.1145/1529282.1529461 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2009-03-08 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Learning Computed tomography Healthcare applications Radiology Teleradiology |
| Content Type | Text |
| Resource Type | Article |
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