ArticleNature communications2022
Deep learning empowered volume delineation of whole-body organs-at-risk for accelerated radiotherapy.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
85 citing papers in PubMed.
- APEX-NET: automated pancreatic evaluation network using early non-contrast CT.European radiology · 2026Article
- A single-arm prospective phase I trial of 68Ga-PFBC01 PET/CT for multiple myeloma B cell maturation antigen imaging.The Journal of clinical investigation · 2026Article
- Cross-fraction prior learning for scalable organ-at-risk segmentation in abdominal MR-guided radiotherapy.Medical physics · 2026Article
- Radiotherapy quality assurance in the PRO-GLIO trial: results from a dummy run comparing experts across twelve institutions in two Scandinavian countries.Clinical and translational radiation oncology · 2026Article
- Radiation oncology at a new frontier: Hotspots, challenges, and emerging advances.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2026Article
- FS-Mamba: Feature-wise scanning Mamba UNet for automatic image segmentation in liver tumor radiotherapy.Journal of applied clinical medical physics · 2026Article
- Diagnostic CT-guided online adaptive radiotherapy for locally advanced colon cancer: a prospective implementation and feasibility study.Clinical and translational radiation oncology · 2026Article
- HAR-Net: Automatic delineation of clinical target volumes for cervical cancer guided by hierarchical anatomical refinement.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026Article
- Neuroimaging-clinical phenotypes are associated with functional outcomes in acute ischemic stroke: a latent class analysis of multidimensional biomarkers.Neuroradiology · 2026Article
- Dysfunction of cerebrospinal fluid circulation and neurovascular decoupling in end-stage renal disease patients with mild cognitive impairment.GeroScience · 2026Article
- PET/CT-based quantification of intratumoral heterogeneity for predicting pathological complete response in breast cancer patients treated with neoadjuvant chemotherapy: A multicentre study.European journal of nuclear medicine and molecular imaging · 2026Article
- Role of high-density area score in predicting outcomes of large-vessel occlusion stroke after endovascular treatment.European radiology · 2026Article
- Application of a multimodal MRI model integrating radiomics and habitat features for predicting glioma pathology and prognosis.BMC medical imaging · 2026Article
- A human-AI collaborative workflow for improved gross tumor volume delineation in esophageal cancer radiotherapy.BMC medical imaging · 2026Article
- Artificial Intelligence Tools in Precision Lung Cancer Care: From Early Detection to Clinical Decision Support.Cancers · 2026Review
- Multi-organ glucose metabolism alterations in diabetes mellitus: a total-bodyEJNMMI research · 2026Article
- A prospective multicenter trial of deep learning auto-segmentation for organs at risk in thoracic radiotherapy.Nature communications · 2026Observational
- Automatic identification of different stage of Alzheimer's disease using multimodal MRI and artificial intelligence.BMC medical imaging · 2026Article
- Educational Impact of a National Training Webinar on AI-based Automatic Contouring in Radiation Oncology.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026Article
- MRI In Vivo Detection of Amyloid-β Protein Deposition in Different Brain Regions of Patients with AD and MCI.Brain topography · 2026Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In radiotherapy for cancer patients, an indispensable process is to delineate organs-at-risk (OARs) and tumors. However, it is the most time-consuming step as manual delineation is always required from radiation oncologists. Herein, we propose a lightweight deep learning framework for radiotherapy treatment planning (RTP), named RTP-Net, to promote an automatic, rapid, and precise initialization of whole-body OARs and tumors. Briefly, the framework implements a cascade coarse-to-fine segmentation, with adaptive module for both small and large organs, and attention mechanisms for organs and boundaries. Our experiments show three merits: 1) Extensively evaluates on 67 delineation tasks on a large-scale dataset of 28,581 cases; 2) Demonstrates comparable or superior accuracy with an average Dice of 0.95; 3) Achieves near real-time delineation in most tasks with <2 s. This framework could be utilized to accelerate the contouring process in the All-in-One radiotherapy scheme, and thus greatly shorten the turnaround time of patients.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.