The Cancer Imaging Archive (TCIA)
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Latest posts
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From Shared Data to Better AI: How TCIA Helped Enable the MAMA-MIA Challenge
What happens to research data after the study that produced it is complete? The MAMA-MIA Challenge offers a compelling answer: when high-quality cancer imaging data are preserved and shared, their scientific value can continue to grow, supporting new questions, collaborations,…
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Meet the TCIA Dataset Explorer: A Smarter Way to Search Medical Imaging Datasets
The Cancer Imaging Archive (TCIA) has long been a cornerstone resource for researchers who rely on high-quality, well-curated medical imaging datasets. As the TCIA catalog has grown to encompass diverse imaging collections, analysis results, and multimodal data, the need for a…
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Connecting Cancer Imaging and Genomics with New GDC–IDC Viewer Tools
Cancer researchers increasingly need to explore imaging, genomic, and other molecular data together. A new integration between the NCI Genomic Data Commons (GDC) and Imaging Data Commons (IDC) is making that easier. The post Connecting Cancer Imaging and Genomics with New…
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TCIA Proposal Submission Deadline: August 28, 2026
The Cancer Imaging Archive (TCIA) curates and publishes freely available cancer imaging datasets. The post TCIA Proposal Submission Deadline: August 28, 2026 appeared first on The Cancer Imaging Archive (TCIA) .
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Advancing Cancer Care with AI: Inside the Foundation Models for Pan-cancer Segmentation Challenge
Artificial intelligence (AI) is transforming cancer care, and one of its most promising applications is medical imaging. The Foundation Models for Pan-cancer Segmentation in CT Images Challenge brings together researchers and AI developers to tackle one of the field's most…
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New Dataset: CPTAC-STAD
The Cancer Imaging Archive (TCIA) has recently published the Clinical Proteomic Tumor Analysis Consortium Stomach Adenocarcinoma (CPTAC-STAD) collection. The post New Dataset: CPTAC-STAD appeared first on The Cancer Imaging Archive (TCIA) .
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Reproducibility in Science Symposium
Panel Spotlight: AI Reproducibility, Transparency, and Trust The “AI Science Standards” panel will examine what reproducibility means in the era of AI-driven research. Machine learning and high-throughput analysis have already demonstrated that reproducible science depends on…
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New Dataset Release: The UC San Diego Longitudinal Vestibular Schwannoma Dataset
The Cancer Imaging Archive (TCIA) is excited to announce the release of the University of California San Diego Longitudinal Vestibular Schwannoma (UCSD-VS-Longitudinal) Dataset, a comprehensive new resource for studying the progression and treatment response of vestibular…
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New Dataset on TCIA: Segmentation of Spinal Multiple Myeloma Lesions in Dual-Energy CT Collection
While significant advancements have been made in applying artificial intelligence to medical imaging, developing robust detection and segmentation algorithms often requires large, precisely annotated datasets. In the context of multiple myeloma, evaluating the extent of bone…
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Evolving The Cancer Imaging Archive: A New Hybrid Infrastructure for Open Science
We’re upgrading our architecture to comply with new NIH policies and better integrate with the NCI Cancer Research Data Commons. The post Evolving The Cancer Imaging Archive: A New Hybrid Infrastructure for Open Science appeared first on The Cancer Imaging Archive (TCIA) .