Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

Meghan W Macomber
Meghan W Macomber
Ivan Tarapov
Ivan Tarapov
David Carter
David Carter

Physics in medicine and biology, Volume 63, Issue 23, 2018, Pages 235002

Cited by: 7|Bibtex|Views43|Links
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Abstract:

Machine learning for image segmentation could provide expedited clinic workflow and better standardization of contour delineation. We evaluated a new model using deep decision forests of image features in order to contour pelvic anatomy on treatment planning CTs. 193 CT scans from one UK and two US institutions for patients undergoing rad...More

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