ReviewPhysica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)2021
A review of deep learning based methods for medical image multi-organ segmentation.
Review in Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
78 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Recent advances in applying machine learning to proton radiotherapy.Biomedical physics & engineering express · 2025Pooled it
- Deep learning in MRI-guided radiation therapy: A systematic review.Journal of applied clinical medical physics · 2024Pooled it
- AI-Based Multi-Organ Segmentation in Gynecologic Laparoscopy: Comparative Evaluation of Deep Learning Architectures for Anatomical Precision and Surgical Applicability.Journal of imaging informatics in medicine · 2026Article
- SynAPSeg: A novel dataset and image analysis framework for deep learning-based synapse detection and quantification.PLoS computational biology · 2026Article
- MKNet-family architectures for auto-segmentation of the residual pancreas after pancreatic resection: a deep learning comparative study.Abdominal radiology (New York) · 2026Article
- Automated detection and characterization of small cell lung cancer liver metastasis on computed tomography.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Article
- Artificial intelligence (AI)-based multi-organ contour quality assurance with uncertainty estimation for online adaptive radiotherapy (oART).Machine Learning. Health · 2026Article
- Fluoroscopy-Guided Motion Management in Particle Therapy: Evolution, Challenges, and AI-Enabled Opportunities.Tomography (Ann Arbor, Mich.) · 2026Review
- Multimodal combined model integrating 2.5D deep learning and habitat radiomics for malignancy discrimination in ≤2 cm BI-RADS 4 breast lesions.Quantitative imaging in medicine and surgery · 2026Article
- SynAPSeg: A novel dataset and image analysis framework for deep learning-based synapse detection and quantification.bioRxiv : the preprint server for biology · 2026Article
- Habitat-aware radiomics and adaptive 2.5D deep learning predict treatment response and long-term survival in ESCC patients undergoing neoadjuvant chemoimmunotherapy.European journal of nuclear medicine and molecular imaging · 2026Article
- A method for magnetic resonance splenomegaly image segmentation based on large-kernel multi-scale attention mechanism.Scientific reports · 2026Article
- MAAR-Net: Multi-scale attention-assisted residual neural network for renal microvascular structure segmentation.PloS one · 2026Article
- Performance enhancement method by using the probabilistic estimation for kidney tumor segmentation.Frontiers in oncology · 2026Article
- Intraoperative use of mixed reality (MR) in humans across surgical disciplines: a major review.3D printing in medicine · 2025Article
- Deep learning for multi-modal medical image segmentation: a survey and comparative study.Brain imaging and behavior · 2025Article
- Deep Learning Model for Volume Measurement of the Remnant Pancreas After Pancreaticoduodenectomy and Distal Pancreatectomy.Diagnostics (Basel, Switzerland) · 2025Article
- Artificial Intelligence Applications in Musculoskeletal Imaging.Current reviews in musculoskeletal medicine · 2025Review
- Large ore detection in blasting piles using LODM.Scientific reports · 2025Article
- Automated Quantitative Evaluation of Age-Related Thymic Involution on Plain Chest CT.Annals of biomedical engineering · 2025Article
18 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
6 authors.
Funding
Abstract
Deep learning has revolutionized image processing and achieved the-state-of-art performance in many medical image segmentation tasks. Many deep learning-based methods have been published to segment different parts of the body for different medical applications. It is necessary to summarize the current state of development for deep learning in the field of medical image segmentation. In this paper, we aim to provide a comprehensive review with a focus on multi-organ image segmentation, which is crucial for radiotherapy where the tumor and organs-at-risk need to be contoured for treatment planning. We grouped the surveyed methods into two broad categories which are 'pixel-wise classification' and 'end-to-end segmentation'. Each category was divided into subgroups according to their network design. For each type, we listed the surveyed works, highlighted important contributions and identified specific challenges. Following the detailed review, we discussed the achievements, shortcomings and future potentials of each category. To enable direct comparison, we listed the performance of the surveyed works that used thoracic and head-and-neck benchmark datasets.
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What Socratic 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 Socratic graph.