Automated pelvic MRI measurements associated with urinary incontinence for prostate cancer patients undergoing radical prostatectomy.

Ingeborg van den BergRobert N SpaansFrank J WesselsErik J R J van der HoevenCharlotte J Tutein NoltheniusRoderick C N van den BerghJochem R N van der Voort van ZypCornelis A T van den BergHarm H E van Melick

Published in: European radiology experimental (2024)

• DL-generated segmentations improve interobserver agreement for pelvic measurements among radiologists. • Membranous urethral length measurement improved from substantial to almost perfect agreement. • Artificial intelligence enhances objective pelvic parameter assessment for continence prediction models.

Keyphrases

urinary incontinence
artificial intelligence
radical prostatectomy
prostate cancer
machine learning
deep learning
rectal cancer
patients undergoing
big data
contrast enhanced
high throughput
computed tomography