TY  - JOUR
SN  - 2052-4463
A1  -  Holmlund William
A1  -  Simkó Attila
A1  -  Söderkvist Karin
A1  -  Palásti Péter
A1  -  Tótin Szilvia
A1  -  Kalmár Kamilla
A1  -  Domoki Zsófia
A1  -  Fejes Zsuzsanna
A1  -  Kincses Zsigmond Tamás
A1  -  Brynolfsson Patrik
A1  -  Nyholm Tufve
N2  - Manual segmentations are considered the gold standard for ground truth in machine learning applications. Such tasks are tedious and time-consuming, albeit necessary to train reliable models. In this work, we present a dataset with expert segmentations of the prostatic zones and urethra for 200 randomly selected patients from the PROSTATEx dataset. Notably, independent duplicate segmentations were performed for 40 patients, providing inter-reader variability data. This results in a total of 240 segmentations. This dataset can be used to train machine learning models or serve as an external test set for evaluating models trained on private data, thereby addressing a current gap in the field. The delineated structures and terminology adhere to the latest Prostate Imaging Reporting and Data Systems v2.1 guidelines, ensuring consistency.
AV  - public
UR  - https://doi.org/10.1038/s41597-024-03945-2
Y1  - 2024///
EP  - 5
TI  - ProstateZones ? Segmentations of the prostatic zones and urethra for the PROSTATEx dataset
ID  - publicatio34850
IS  - 1
VL  - 11
JF  - SCIENTIFIC DATA
ER  -