Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps.

To evaluate short-term test-retest repeatability of a deep learning architecture (U-Net) in slice- and lesion-level detection and segmentation of clinically significant prostate cancer (csPCa: Gleason grade group > 1) using diffusion-weighted imaging fitted with monoexponential function, ADCm.

PET imaging in urology: a rapidly growing successful collaboration.

To discuss and highlight the recent findings in urological oncology focusing on nuclear medicine advances on imaging and therapy. Testicular tumors: F-FDG as the standard positron emission tomography (PET) tracer with proven good accuracy in detecting metastatic testicular cancer; urothelial cancer: good accuracy of F-FDG PET in detecting distant metastases but poor results in detecting […]

COVID-19 Round 3 – Oliver Sartor – 1854

Alicia Morgans: Hi, this is Alicia Morgans, Associate Professor of Medicine and GU Medical Oncologist at Northwestern University in Chicago, Illinois. I am so grateful to have here with me today, Dr. Oliver Sartor, who is a Professor of Medicine and the Medical Director at the Tulane Cancer Center in New Orleans in Louisiana. Thank you […]

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