Deep learning algorithms for automated assessment of total and cancerous prostate gland volume based on PET/CT

Conclusions: Our deep learning based method for fast automated analysis of the prostate gland in PET/CT studies showed good agreement with manually obtained measurements and pathology-derived weight of the prostatectomy specimens suggesting that this approach may become a promising adjunct to quantitative assessment of PET/CT studies in prostate cancer patients. The method is now open for validation in future prospective clinical trials.

Source: Journal of Nuclear Medicine - May 23, 2018 Category: Nuclear Medicine Authors: Borrelli, P., Mortensen, M., Enqvist, O., Ulen, J., Poulsen, M., Tragardh, E., Hoilund-Carlsen, P. F., Edenbrandt, L. Tags: Prostate Posters Source Type: research