Overcoming generative likelihood bias for voxel-based out-of-distribution detection
Deep learning-based dose prediction is a promising approach to automated radiotherapy planning but carries with it the risk of failing silently when the inputs are highly abnormal compared to the training data. One way to address this issue is to develop a dedicated outlier detector capable of detec...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-304326 |