ReviewJournal of healthcare engineering2022
U-Net-Based Medical Image Segmentation.
Review in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 84 papers, 1 of them a synthesis that pooled it.
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
84 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning for classifying the stages of periodontitis on dental images: a systematic review and meta-analysis.BMC oral health · 2023Pooled it
- Automated extraction of the plane of minimal hiatal dimensions and mid-sagittal plane from 3D transperineal ultrasound.Medical physics · 2026Article
- Self-Supervised Transformer-Based Pipeline for Liver Tumor Segmentation and Type Classification.JCO clinical cancer informatics · 2026Article
- BrainView: A cloud-based deep learning system for brain image segmentation, tumor detection and visualization.Biomedical journal · 2026Article
- An end-to-end deep-learning system for segmentation and classification of dental caries from radiovisiography images.Journal of conservative dentistry and endodontics · 2025Article
- Panoramic Nailfold Flow Velocity Measurement Method Based on Enhanced Plasma Gap Information.Journal of imaging informatics in medicine · 2025Article
- A superpixel based self-attention network for uterine fibroid segmentation in high intensity focused ultrasound guidance images.Scientific reports · 2025Article
- Near-zero photon bioimaging by fusing deep learning and ultralow-light microscopy.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Artificial intelligence-based pulmonary vessel segmentation: an opportunity for automated three-dimensional planning of lung segmentectomy.Interdisciplinary cardiovascular and thoracic surgery · 2025Article
- Article
- Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function.Nature methods · 2025Article
- Automated measurement of cardiothoracic ratio based on semantic segmentation integration model using deep learning.Medical & biological engineering & computing · 2025Article
- Cherenkov Imaged Bio-Morphological Features Verify Patient Positioning With Deformable Tissue Translocation in Breast Radiation Therapy.Advances in radiation oncology · 2025Article
- Development and evaluation of a deep learning framework for pelvic and sacral tumor segmentation from multi-sequence MRI: a retrospective study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Applications of Artificial Intelligence, Deep Learning, and Machine Learning to Support the Analysis of Microscopic Images of Cells and Tissues.Journal of imaging · 2025Review
- Prediction of biochemical prostate cancer recurrence from any Gleason score using robust tissue structure and clinically available information.Discover oncology · 2025Article
- Multistage deep learning methods for automating radiographic sharp score prediction in rheumatoid arthritis.Scientific reports · 2025Article
- Automatic segmentation of white matter lesions on multi-parametric MRI: convolutional neural network versus vision transformer.BMC neurology · 2025Article
- Application of deep learning convolutional neural networks to identify gastric squamous cell carcinoma in mice.Frontiers in medicine · 2025Article
- Analysis of breast region segmentation in thermal images using U-Net deep neural network variants.Frontiers in bioinformatics · 2025Article
24 more citing papers are in PubMed but not listed here.
Corrections and comments
- Retraction · 2023-10-18Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep learning has been extensively applied to segmentation in medical imaging. U-Net proposed in 2015 shows the advantages of accurate segmentation of small targets and its scalable network architecture. With the increasing requirements for the performance of segmentation in medical imaging in recent years, U-Net has been cited academically more than 2500 times. Many scholars have been constantly developing the U-Net architecture. This paper summarizes the medical image segmentation technologies based on the U-Net structure variants concerning their structure, innovation, efficiency, etc.; reviews and categorizes the related methodology; and introduces the loss functions, evaluation parameters, and modules commonly applied to segmentation in medical imaging, which will provide a good reference for the future research.
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.