SHAO-LUN LULiao, Heng-ChunHeng-ChunLiaoFENG-MING HSULiao, Chun-ChihChun-ChihLiaoFEI-PEI LAIFU-REN XIAO2022-02-172022-02-172021-12-011053-8119https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115425707&doi=10.1016%2fj.neuroimage.2021.118585&partnerID=40&md5=7e429d09e9174a41dd8813465c9e3f8bhttps://scholars.lib.ntu.edu.tw/handle/123456789/594655We report the set-up of the Intracranial Tumor Segmentation (ICTS) dataset. This dataset was retrieved from clinical work of radiosurgery, contoured by qualified neurosurgeons and radiation oncologists. It contains contrast-enhanced T1-weighted images of 1500 patients, together with the labels of tumors to be treated. The ICTS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource. © 2021 The Author(s)Benchmark; Brain; Image segmentation; MRI; Oncology/tumor[SDGs]SDG3adolescent; adult; aged; Article; benchmarking; cancer patient; child; contrast enhancement; controlled study; female; human; image segmentation; intracranial tumor; major clinical study; male; neuroimaging; neurosurgeon; nuclear magnetic resonance imaging; online system; qualitative analysis; radiation oncologist; radiosurgery; brain; brain tumor; diagnostic imaging; image enhancement; information processing; neuroimaging; nuclear magnetic resonance imaging; procedures; Benchmarking; Brain; Brain Neoplasms; Datasets as Topic; Humans; Image Enhancement; Magnetic Resonance Imaging; Neuroimaging; Online Systems; Radiosurgeryjournal article10.1016/j.neuroimage.2021.118585345602722-s2.0-85115425707