Pneumonia Detection on Chest X-rays with Attention Mask Data Augmentation

Fengwei Lai, Seiichiro Kamata, Zhengbo Luo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Each year, pneumonia affects about 450 million people globally and results in about 4 million deaths. In developing countries, pneumonia remains a leading cause of death in chronic patients and older adults. Chest X-rays are currently the best available method for diagnosing pneumonia, which is very critical for the treatment of patients. Deep learning-based image recognition technology can significantly improve the efficiency of pneumonia detection. Data Augmentation is a technology that artificially expands the training data set by using limited data to generate more comparable data. Excellent data augmentation methods can effectively improve the performance of neural networks and are currently widely used in various fields of deep learning. We propose a novel data augmentation method called Attention Mask in this paper, which provides accurate predictions and a more explainable attention focus comparing with many traditional data augmentation methods, such as random erasing and hide-and-seek. We guide the weight and focal point of the model with the attention mechanism to avoid the model from relying too much on superficial features. After data augmentation, the self-ensemble of different stage models also makes the entire system more stable. The experiments show that the attention is reasonably diverted, which is extremely helpful in classifying the target that is fallibility correctly. On Chest X-Ray Images (Pneumonia) dataset for classification, our method notably improves performance over baselines.

Original languageEnglish
Title of host publicationProceedings of 2020 2nd International Conference on Video, Signal and Image Processing, VSIP 2020
PublisherAssociation for Computing Machinery
Pages10-16
Number of pages7
ISBN (Electronic)9781450388931
DOIs
Publication statusPublished - 2020 Apr 12
Event2nd International Conference on Video, Signal and Image Processing, VSIP 2020 - Virtual, Online, Indonesia
Duration: 2020 Dec 42020 Dec 6

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2nd International Conference on Video, Signal and Image Processing, VSIP 2020
CountryIndonesia
CityVirtual, Online
Period20/12/420/12/6

Keywords

  • Data augmentation
  • Information deletion
  • Pneumonia detection

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Fingerprint Dive into the research topics of 'Pneumonia Detection on Chest X-rays with Attention Mask Data Augmentation'. Together they form a unique fingerprint.

Cite this