Pablo Borrelli
Goeteborg, O 41345, Sweden
Last Updated: 09/26/2026
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Found 13 publications
AI-based fully automatic image analysis: Optimal abdominal and thoracic segmentation volumes for estimating total muscle volume on computed tomography scans.
Journal: Osteoporosis and sarcopenia
Published: November 07, 2023
Analytical performance validation of aPROMISE platform for prostate tumor burden, index and dominant tumor assessment with 18F-DCFPyL PET/CT. A pilot study.
Journal: Scientific reports
Published: September 16, 2023
Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [18F]-PSMA-1007 PET-CT.
Journal: Diagnostics (Basel, Switzerland)
Published: August 01, 2022
Automated classification of PET-CT lesions in lung cancer: An independent validation study.
Journal: Clinical physiology and functional imaging
Published: January 28, 2022
Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients.
Journal: Scandinavian journal of urology
Published: September 27, 2021
Freely available convolutional neural network-based quantification of PET/CT lesions is associated with survival in patients with lung cancer.
Journal: EJNMMI physics
Published: June 06, 2021
Automated artificial intelligence-based analysis of skeletal muscle volume predicts overall survival after cystectomy for urinary bladder cancer.
Journal: European radiology experimental
Published: May 19, 2021
AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients.
Journal: EJNMMI physics
Published: September 08, 2020
Artificial intelligence-aided CT segmentation for body composition analysis: a validation study.
Journal: European radiology experimental
Published: August 25, 2020
Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival.
Journal: Clinical physiology and functional imaging
Published: June 10, 2020
RECOMIA-a cloud-based platform for artificial intelligence research in nuclear medicine and radiology.
Journal: EJNMMI physics
Published: February 22, 2020
Deep learning-based quantification of PET/CT prostate gland uptake: association with overall survival.
Journal: Clinical physiology and functional imaging
Published: May 21, 2019
Last Updated: 09/26/2026