University of Lund Prostate Cancer Dataset

Overview:Radiotherapy treatment for prostate cancer relies on computed tomography (CT) and/or magnetic resonance imaging (MRI) for delineation of radiation targets and organs at risk (OARs). Manual delineation of these volumes is regarded as the gold standard for ground truth in machine learning applications, but to acquire such data is tedious and time-consuming. The LUND‑PROBE dataset (doi:10.23698/aida/lund‑probe) is a clinical dataset, comprising MRI images, synthetic CT (sCT) images, target and OARs delineations, and radiotherapy dose distributions for 432 prostate cancer patients treated with an MRI-only radiotherapy workflow. An extended dataset with 35 patients is also included, containing the data mentioned above together with deep learning (DL)-generated delineations, DL uncertainty maps, and DL structures manually edited by four radiation oncologists. The publication of these resources aims to aid research within the fields of automated radiotherapy planning and structure delineation, inter-observer analyses, and DL uncertainty investigation. More details about this project can be found here: https://www.nature.com/articles/s41597-025-04954-5Data usage:UOM has obtained permission to use this dataset for medical-related research projects. As stated in the research agreement (https://drive.google.com/file/d/16r1evab5ocxQ4xfN7DEzVd4BXkE82srL/view?usp=sharing), access to the data requires prior approval. If you would like to make use of this dataset for your research project, please contact Dr. Susan Mercieca at [e-mail] and provide a brief description of your intended use.