Verio 3.0 tesla t

The experimental data were collected during clinical prostate examinations in the hospital from July 2012 to June 2018. Data were collected for a total of 220 patients, including 121 healthy subjects and 99 prostate cancer patients, and were processed anonymously. All of prostate MRI images were acquired on a 3.0-T MR imaging system (SIEMENS Verio 3.0 Tesla (T)), and the running software version is syngo MR B17. Transverse T2-weighted (T2-w) images were acquired using Turbo spin-echo sequence with the following parameters: repetition time, 2900-4030 ms; echo time, 96-106 ms; slick thickness, 3-4.0 mm; intersection gap, 3.6-4.8 mm; and matrix, 640×640. Prostate boundary masks were cross-labeled by two expert clinicians with more than five years clinical experience, and labeled images used as the ground truth in the form of binary masks.
To verify the generalizability of the model, we used the public dataset PROMISE12, which was provided by 2012 MICCAI challenges [31] . Although the images in the dataset were collected using different devices with different resolutions and scan protocols, the data has greater universality, and it was not used in the training process. Thus, we considered 20 randomly selected MRI images from this dataset as suitable for verifying the generalizability of our model. These images were all as large as those in the clinical test dataset.