A new editorial paper published in Oncoscience discusses the use of deep learning-assisted lesion segmentation in PET/CT imaging for salvage radiation therapy in prostate cancer. Prostate cancer remains a significant challenge despite advancements in treatment outcomes. Salvage radiation therapy is often offered to patients with recurrent disease post-initial treatments. Traditional imaging modalities have limitations in accurately detecting and determining the volume of recurrent disease, but 18F-fluciclovine PET/CT has shown promise in improving salvage disease management. The editorial explores the feasibility of using deep learning models for lesion segmentation on 18F-fluciclovine PET/CT images, which could enhance treatment quality compared to manual contouring. The study highlights the potential of AI algorithms in medical image processing for precision medicine in prostate cancer care. Oncoscience is a peer-reviewed journal covering cancer research and is free for both readers and authors. The use of deep learning in lesion segmentation for salvage radiation therapy planning shows promise in improving treatment outcomes for prostate cancer patients.
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Source link: https://www.eurekalert.org/news-releases/1049933
Segmenting lesions using deep learning technology for medical purposes. #MedicalAI
