Dataset
cancer, cervical cancer
CANCER, CERVICAL CANCER
Since there is no publicly available training dataset specific for the task of image alignment, a large dataset of the female pelvis was collected for the inter-fraction deformation simulation. Fifty-seven patients with cervical cancer diagnosed at the cancer institute of this study between 2017 and 2018 were included in this study. The collected data included planning CT images and the corresponding RT structure data. For each patient, a CT scan was acquired in the supine position from about L5 vertebrae to the femoral heads. All images were taken by the same CT scanner (SOMATOM Scope CT scan, Siemens Healthcare, Forchheim, Germany). All CT images were acquired with the same acquisition protocol (KVp = 110 and mAs = 130). Image dimension was set at 512 × 512 for each trans-axial slice with about 80–150 slices with a pixel spacing of 0.84 mm and a slice thickness of 5 mm. In total, there were 7202 2D CT images. The RT structure data, in the form of manually defined contours for each organ, were delineated by a physician for the bladder, rectum, and cervix. The study protocol was approved by the ethical guidelines. The datasets of 57 patients were randomly divided into a 42-patient training set and a 15-patient test set.