Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification
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Summary
A three-branch attention guided convolution neural network (AG-CNN) that learns from disease-specific regions to avoid noise and improve alignment, and also integrates a global branch to compensate the lost discriminative cues by local branch.
- Type
- preprint
- Published
- 2018-01-30
- Cited by
- 290
- References
- 40
- Access
- Open access
- OpenAlex
- https://openalex.org/W2786052267
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:30298694
Keywords
Convolutional neural network, Discriminative model, Artificial intelligence, Computer science, Pooling
References
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- Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
- Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation
- AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images
- Learning what to look in chest X-rays with a recurrent visual attention model
- A survey on deep learning in medical image analysis
- Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks With Jaccard Distance
- ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases
Cited by
- Weakly Supervised Medical Diagnosis and Localization from Multiple Resolutions
- Large Scale Automated Reading of Frontal and Lateral Chest X-Rays using Dual Convolutional Neural Networks
- Weakly Supervised Deep Learning for Thoracic Disease Classification and Localization on Chest X-rays
- Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images
- Computer-aided detection in chest radiography based on artificial intelligence: a survey
- Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs
- Multi-label chest X-ray image classification via category-wise residual attention learning
- Finding a Needle in the Haystack: Attention-Based Classification of High Resolution Microscopy Images
- Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
- CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
- Deep Learning with Attention to Predict Gestational Age of the Fetal Brain
- PadChest: A large chest x-ray image dataset with multi-label annotated reports
- Chest X-Rays Image Classification in Medical Image Analysis
- Dense networks with relative location awareness for thorax disease identification.
- DualCheXNet: dual asymmetric feature learning for thoracic disease classification in chest X-rays
- A Novel Approach for Multi-Label Chest X-Ray Classification of Common Thorax Diseases
- Multi-task Learning for Chest X-ray Abnormality Classification on Noisy Labels
- Feasibility of Automated Deep Learning Design for Medical Image Classification by Healthcare Professionals with Limited Coding Experience
- Combining LSTM and DenseNet for Automatic Annotation and Classification of Chest X-Ray Images
- Automatic Lung Cancer Prediction from Chest X-ray Images Using the Deep Learning Approach
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