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Tristan Barrett

Showing results (41-50 of 185) with videos related to

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Wiley Interdisciplinary Reviews. Nanomedicine and Nanobiotechnology|January 6, 2010
Nanoparticles in sentinel lymph node mappingGregory Ravizzini, Baris Turkbey, Tristan Barrett, et al.
BJU International|December 1, 2018
Using prognosis to guide early detection and treatment selection in non-metastatic prostate cancerVincent J Gnanapragasam, Tristan Barrett, Charlie Massie, et al.
European Radiology|April 24, 2024
Biparametric MRI in prostate cancer during active surveillance: is it safe?Iztok Caglic, Nikita Sushentsev, Tom Syer, et al.
The British Journal of Radiology|August 6, 2021
Optimal biopsy approach for detection of clinically significant prostate cancerSimona Ippoliti, Peter Fletcher, Luca Orecchia, et al.
Cancers|November 27, 2025
Improving the Potential for Predicting Prostate Cancer Progression in Patients on Active Surveillance Using Explainable Artificial IntelligenceOlga Vershinina, Nikita Sushentsev, Alexey Zaikin, et al.
Communications Engineering|November 29, 2025
Object detection as an aid for locating the prostate in surface-based abdominal ultrasound imagesRory D Bennett, Tristan Barrett, Vincent J Gnanapragasam, et al.
Radiology|April 5, 2012
Value of the hemorrhage exclusion sign on T1-weighted prostate MR images for the detection of prostate cancerTristan Barrett, Hebert Alberto Vargas, Oguz Akin, et al.
Plos One|January 29, 2021
Reproducibility of magnetic resonance fingerprinting-based T1 mapping of the healthy prostate at 1.5 and 3.0 T: A proof-of-concept studyNikita Sushentsev, Joshua D Kaggie, Rhys A Slough, et al.
European Journal of Radiology|June 7, 2017
Evaluating the effect of rectal distension on prostate multiparametric MRI image qualityIztok Caglic, Nienke L Hansen, Rhys A Slough, et al.
Scientific Reports|June 22, 2021
MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillanceNikita Sushentsev, Leonardo Rundo, Oleg Blyuss, et al.
Pageof 19

Showing results (41-50 of 185) with videos related to

Sort By:
Pageof 19
Wiley Interdisciplinary Reviews. Nanomedicine and Nanobiotechnology|January 6, 2010
Nanoparticles in sentinel lymph node mappingGregory Ravizzini, Baris Turkbey, Tristan Barrett, et al.
BJU International|December 1, 2018
Using prognosis to guide early detection and treatment selection in non-metastatic prostate cancerVincent J Gnanapragasam, Tristan Barrett, Charlie Massie, et al.
European Radiology|April 24, 2024
Biparametric MRI in prostate cancer during active surveillance: is it safe?Iztok Caglic, Nikita Sushentsev, Tom Syer, et al.
The British Journal of Radiology|August 6, 2021
Optimal biopsy approach for detection of clinically significant prostate cancerSimona Ippoliti, Peter Fletcher, Luca Orecchia, et al.
Cancers|November 27, 2025
Improving the Potential for Predicting Prostate Cancer Progression in Patients on Active Surveillance Using Explainable Artificial IntelligenceOlga Vershinina, Nikita Sushentsev, Alexey Zaikin, et al.
Communications Engineering|November 29, 2025
Object detection as an aid for locating the prostate in surface-based abdominal ultrasound imagesRory D Bennett, Tristan Barrett, Vincent J Gnanapragasam, et al.
Radiology|April 5, 2012
Value of the hemorrhage exclusion sign on T1-weighted prostate MR images for the detection of prostate cancerTristan Barrett, Hebert Alberto Vargas, Oguz Akin, et al.
Plos One|January 29, 2021
Reproducibility of magnetic resonance fingerprinting-based T1 mapping of the healthy prostate at 1.5 and 3.0 T: A proof-of-concept studyNikita Sushentsev, Joshua D Kaggie, Rhys A Slough, et al.
European Journal of Radiology|June 7, 2017
Evaluating the effect of rectal distension on prostate multiparametric MRI image qualityIztok Caglic, Nienke L Hansen, Rhys A Slough, et al.
Scientific Reports|June 22, 2021
MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillanceNikita Sushentsev, Leonardo Rundo, Oleg Blyuss, et al.
Pageof 19