Deep neural network for automatic characterization of lesions on 68Ga-PSMA-11 PET/CT.PURPOSE
 This study proposes an automated prostate cancer (PC) lesion characterization method based on the deep neural network to determine tumor burden on 68Ga-PSMA-11 PET/CT to potentially facilitate the optimization of PSMA-directed radionuclide therapy.


 A deep neural network (triple-combining 2.5D U-Net) was developed for the automated characterization of these lesions.  We developed a deep neural network to characterize automatically the PC lesions on 68Ga-PSMA-11 PET/CT. 
Deep neural network
Deep neural network for automatic characterization of lesions on 68Ga-PSMA-11 PET/CT.PURPOSE
 This study proposes an automated prostate cancer (PC) lesion characterization method based on the deep neural network to determine tumor burden on 68Ga-PSMA-11 PET/CT to potentially facilitate the optimization of PSMA-directed radionuclide therapy.


 We collected 68Ga-PSMA-11 PET/CT images from 193 patients with metastatic PC at three medical centers.  We developed a deep neural network to characterize automatically the PC lesions on 68Ga-PSMA-11 PET/CT. 
68Ga-PSMA-11 PET/CT
A deep neural network (triple-combining 2.5D U-Net) was developed for the automated characterization of these lesions. 
U-Net