ArticleScientific data2024
SAROS: A dataset for whole-body region and organ segmentation in CT imaging.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- State of abdominal CT datasets: A critical review of bias, clinical relevance, and real-world applicability.PLOS digital health · 2026Review
- Technical performance of L3 skeletal muscle area (SMA) measurement on CT for L3 skeletal muscle index (L3SMI) assessment.Scientific reports · 2026Article
- A Dataset of Abdominal CT with Artery and Vein Segmentations for Colorectal Cancer Surgical Planning.Scientific data · 2026Article
- Sharing a whole-/total-body [Scientific data · 2026Article
- External Validation of an Open-Source Model for Automated Muscle Segmentation in CT Imaging of Cancer Patients.Journal of imaging · 2026Article
- Deep-learning pipeline for automated skeletal muscle segmentation and sarcopenia detection.Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology · 2026Article
- Improved muscle and fat segmentation for body composition measures on quantitative CT.International journal of computer assisted radiology and surgery · 2025Article
- A simple and effective approach for body part recognition on CT scans based on projection estimation.Scientific reports · 2025Article
- Foundation models for radiology-the position of the AI for Health Imaging (AI4HI) network.Insights into imaging · 2025Review
- Sharing a whole-/total-body [18F]FDG-PET/CT dataset with CT-derived segmentations: an ENHANCE.PET initiative.Research square · 2025Article
- KEVS: enhancing segmentation of visceral adipose tissue in pre-cystectomy CT with Gaussian kernel density estimation.International journal of computer assisted radiology and surgery · 2025Article
- AcuSim: A Synthetic Dataset for Cervicocranial Acupuncture Points Localisation.Scientific data · 2025Article
- Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies.Scientific reports · 2025Article
- GIRAFE: Glottal imaging dataset for advanced segmentation, analysis, and facilitative playbacks evaluation.Data in brief · 2025Review
- Image Synthesis in Nuclear Medicine Imaging with Deep Learning: A Review.Sensors (Basel, Switzerland) · 2024Review
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Sparsely Annotated Region and Organ Segmentation (SAROS) dataset was created using data from The Cancer Imaging Archive (TCIA) to provide a large open-access CT dataset with high-quality annotations of body landmarks. In-house segmentation models were employed to generate annotation proposals on randomly selected cases from TCIA. The dataset includes 13 semantic body region labels (abdominal/thoracic cavity, bones, brain, breast implant, mediastinum, muscle, parotid/submandibular/thyroid glands, pericardium, spinal cord, subcutaneous tissue) and six body part labels (left/right arm/leg, head, torso). Case selection was based on the DICOM series description, gender, and imaging protocol, resulting in 882 patients (438 female) for a total of 900 CTs. Manual review and correction of proposals were conducted in a continuous quality control cycle. Only every fifth axial slice was annotated, yielding 20150 annotated slices from 28 data collections. For the reproducibility on downstream tasks, five cross-validation folds and a test set were pre-defined. The SAROS dataset serves as an open-access resource for training and evaluating novel segmentation models, covering various scanner vendors and diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.