ArticleJournal of medical imaging (Bellingham, Wash.)2020
Automatic multi-organ segmentation in computed tomography images using hierarchical convolutional neural network.
Article in Journal of medical imaging (Bellingham, Wash.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 16 citations in OpenAlex.
- Deep CNN-based Fully Automated Segmentation of Pelvic Multi-Organ on CT Images for Prostate Cancer Radiotherapy.Journal of biomedical physics & engineering · 2025Article
- Cascaded cross-attention transformers and convolutional neural networks for multi-organ segmentation in male pelvic computed tomography.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Enhancing Radiotherapy Workflow for Head and Neck Cancer with Artificial Intelligence: A Systematic Review.Journal of personalized medicine · 2023Review
- Dynamic hierarchical multi-scale fusion network with axial MLP for medical image segmentation.Scientific reports · 2023Article
- Cascaded neural network segmentation pipeline for automated delineation of prostate and organs at risk in male pelvic CT.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Deep Learning-Based Segmentation of Head and Neck Organs-at-Risk with Clinical Partially Labeled Data.Entropy (Basel, Switzerland) · 2022Article
- Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network.Journal of applied clinical medical physics · 2022Article
- Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer.Radiation oncology (London, England) · 2022Article
- Fully automated multiorgan segmentation of female pelvic magnetic resonance images with coarse-to-fine convolutional neural network.Medical physics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
PubMed holds no abstract for this paper.
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.