This collection introduces an open-source, anthropomorphic phantom-based dataset of CT scans for developing harmonization methods for deep learning based models. The phantom mimics human anatomy, allowing repeated scans without radiation delivery to real patients and...
We present a dataset of 11,892 longitudinal brain MRI studies from 1,430 patients with clinically confirmed brain metastases. T1-weighted pre-contrast, T1-weighted post-contrast, T2-weighted, and fluid-attenuated inversion recovery MRI sequence images are provided in NIfTI format. Additionally, an Excel spreadsheet with patient demographic information, scanner details, and image acquisition parameters...
These resources comprise a large and diverse collection of multi-site, multi-modality, and multi-cancer clinical DICOM images from 538 subjects infused with synthetic PHI/PII in areas encountered by TCIA curation teams. Also provided is a TCIA-curated version of the synthetic dataset, along with mapping files for mapping identifiers between the two.
This new MIDI data resource includes...
This dataset includes MR imaging from 203 glioma patients with 617 different post-treatment MR time points, and tumor segmentations. Clinical data includes patient demographics, genomics, and treatment details. Preprocessing of MR images followed a standardized pipeline with automatic tumor segmentation based on nnUNet deep learning approach. The automatic...
This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Head-and-Neck cancer (CPTAC-HNSCC) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology...
This dataset consists of 268 T1-post contrast Magnetic Resonance Images (MRIs) in NIfTI format from 165 patients with histologically confirmed metastatic breast cancer to the brain. Some patients underwent repeat Gamma Knife treatments (usually for recurrence), resulting in 268 total studies. Each MRI has a unique identifier to the patient and their treatment session. For example, if a patient had their first treatment...
The Research for Precision Oncology Program (RePOP) is a research activity that established a cohort of Veterans diagnosed with cancer and had genomic analyses performed on their tumor tissue as part of the standard of care. All data relevant to a patient’s cancer and cancer care were collected under RePOP, including patient demographics, comorbidities, genomic analysis, treatments, medications, lab values, imaging...
While there is a growing number of publicly available pre-operative MRI datasets for high-grade gliomas, very few post-operative datasets are available. Here we present the University of California San Diego post-operative high-grade glioma multimodal MRI (UCSD-PTGBM) dataset. The UCSD-PTGBM dataset includes 243 timepoints from 178 subjects (mean age 56 +/- 13 years [std], 116 men, 62 women)...
This dataset was generated to train models for research in the Radiation Planning Assistant (RPA), aimed at auto-contouring cervical lymph node levels in the head and neck.
We provide an annotated imaging dataset of cancerous CT spines to help develop artificial intelligence frameworks for automatic vertebrae segmentation and classification. This collection contains a dataset of 55 CT scans collected on patients with a large range of primary cancers and corresponding bone metastatic lesions obtained for patients with metastatic spine disease. The subjects of the study planned for radiotherapy...
