ArticleApplied soft computing2021
An evolvable adversarial network with gradient penalty for COVID-19 infection segmentation.
Article in Applied soft computing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 51 citations in OpenAlex.
- Dual-branch image projection network for geographic atrophy segmentation in retinal OCT images.Scientific reports · 2025Article
- LcmUNet: A Lightweight Network Combining CNN and MLP for Real-Time Medical Image Segmentation.Bioengineering (Basel, Switzerland) · 2023Article
- Analysis of the Effectiveness of Metaheuristic Methods on Bayesian Optimization in the Classification of Visual Field Defects.Diagnostics (Basel, Switzerland) · 2023Article
- A Novel Deep Learning-Based Classification Framework for COVID-19 Assisted with Weighted Average Ensemble Modeling.Diagnostics (Basel, Switzerland) · 2023Article
- The Synergy between Deep Learning and Organs-on-Chips for High-Throughput Drug Screening: A Review.Biosensors · 2023Review
- Estimation of Caenorhabditis Elegans Lifespan Stages Using a Dual-Path Network Combining Biomarkers and Physiological Changes.Bioengineering (Basel, Switzerland) · 2022Article
- COVID-19 Detection from Chest X-rays Using Trained Output Based Transfer Learning Approach.Neural processing letters · 2022Article
- Unsupervised segmentation and quantification of COVID-19 lesions on computed Tomography scans using CycleGAN.Methods (San Diego, Calif.) · 2022Article
- TSRNet: Diagnosis of COVID-19 based on self-supervised learning and hybrid ensemble model.Computers in biology and medicine · 2022Article
- A Comprehensive Performance Analysis of Transfer Learning Optimization in Visual Field Defect Classification.Diagnostics (Basel, Switzerland) · 2022Article
- CHS-Net: A Deep Learning Approach for Hierarchical Segmentation of COVID-19 via CT Images.Neural processing letters · 2022Article
- Multiparametric Magnetic Resonance Imaging Information Fusion Using Graph Convolutional Network for Glioma Grading.Journal of healthcare engineering · 2022Article
- COV-DLS: Prediction of COVID-19 from X-Rays Using Enhanced Deep Transfer Learning Techniques.Journal of healthcare engineering · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 infection segmentation has essential applications in determining the severity of a COVID-19 patient and can provide a necessary basis for doctors to adopt a treatment scheme. However, in clinical applications, infection segmentation is performed by human beings, which is time-consuming and generally introduces bias. In this paper, we developed a novel evolvable adversarial framework for COVID-19 infection segmentation. Three generator networks compose an evolutionary population to accommodate the current discriminator, i.e., generator networks evolved with different mutations instead of the single adversarial objective to provide sufficient gradient feedback. Compared with the existing work that enforces a Lipschitz constraint by weight clipping, which may lead to gradient exploding or vanishing, the proposed model also incorporates the gradient penalty into the network, penalizing the discriminator's gradient norm input. Experiments on several COVID-19 CT scan datasets verified that the proposed method achieved superior effectiveness and stability for COVID-19 infection segmentation.
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