mlsanityData to 7 Oct 2026

Lung Segmentation from Chest X-rays using Variational Data Imputation

arXiv 2005.10052 ↗First posted 20 May 2020eess.IV cs.CV cs.LGcited by 15

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Abstract (arXiv)

Pulmonary opacification is the inflammation in the lungs caused by many respiratory ailments, including the novel corona virus disease 2019 (COVID-19). Chest X-rays (CXRs) with such opacifications render regions of lungs imperceptible, making it difficult to perform automated image analysis on them. In this work, we focus on segmenting lungs from such abnormal CXRs as part of a pipeline aimed at automated risk scoring of COVID-19 from CXRs. We treat the high opacity regions as missing data and present a modified CNN-based image segmentation network that utilizes a deep generative model for data imputation. We train this model on normal CXRs with extensive data augmentation and demonstrate the usefulness of this model to extend to cases with extreme abnormalities.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 May 2020.

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Citing papers per year: 2021: 6; 2022: 3; 2023: 1; 2024: 4; 2025: 1.

15 papers.

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  1. 2021Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencodercited by 27
  2. 2021Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessmentcited by 6
  3. 2022Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factorscited by 6
  4. 2021CXR Segmentation by AdaIN-based Domain Adaptation and Knowledge Distillationcited by 2
  5. 2021CXR-Net: An Encoder-Decoder-Encoder Multitask Deep Neural Network for Explainable and Accurate Diagnosis of COVID-19 pneumonia with Chest X-ray Imagescited by 1
  6. 2023Self-Supervised Curricular Deep Learning for Chest X-Ray Image Classificationcited by 1
  7. 2025Prompt-Aware Adaptive Elastic Weight Consolidation for Continual Learning in Medical Vision-Language Modelscited by 1
  8. 2021Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentationscited by 0
  9. 2021CXR-Net: An Artificial Intelligence Pipeline for Quick Covid-19 Screening of Chest X-Rayscited by 0
  10. 2022Enhancing Generative Networks for Chest Anomaly Localization through Automatic Registration-Based Unpaired-to-Pseudo-Paired Training Data Translationcited by 0
  11. 2022Confidence-Guided Data Augmentation for Improved Semi-Supervised Trainingcited by 0
  12. 2024Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomographycited by 0
3 more
  1. 2024A comparative analysis of deep learning models for lung segmentation on X-ray imagescited by 0
  2. 2024Mitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schemacited by 0
  3. 2024Cartesian Genetic Programming Approach for Designing Convolutional Neural Networkscited by 0