The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Identifying pneumonia in chest X-rays: A deep learning approach
Abstract
Abstract The rich collection of annotated datasets piloted the robustness of deep learning techniques to effectuate the implementation of diverse medical imaging tasks. Over 15% of deaths include children under age five are caused by pneumonia globally. In this study, we describe our deep learning based approach for the identification and localization of pneumonia in Chest X-rays (CXRs) images. Researchers usually employ CXRs for the diagnostic imaging study. Several factors such as positioning of the patient and depth of inspiration can change the appearance of the chest X-ray, complicating interpretation further. Our identification model ( https://github.com/amitkumarj441/identify_pneumonia ) is based on Mask-RCNN, a deep neural network which incorporates global and local features for pixel-wise segmentation. Our approach achieves robustness through critical modifications of the training process and a novel post-processing step which merges bounding boxes from multiple models. The proposed identification model achieves better performances evaluated on chest radiograph dataset which depict potential pneumonia causes.
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Cites
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Cited by
Narin, A., Kaya, C., & Pamuk, Z. (2021) · Pattern Analysis and Applications · doi:10.1007/s10044-021-00984-y · Cited by 2,054
A Novel Transfer Learning Based Approach for Pneumonia Detection in Chest X-ray Images
Chouhan, V., Singh, S. K., Khamparia, A., Gupta, D., Tiwari, P., Moreira, C., Damaševičius, R., & de Albuquerque, V. H. C. (2020) · Applied Sciences · doi:10.3390/app10020559 · Cited by 753
Self-citationToraman, S., Alakus, T. B., & Turkoglu, I. (2020) · Chaos, Solitons & Fractals · doi:10.1016/j.chaos.2020.110122 · Cited by 327
Pneumonia detection in chest X-ray images using convolutional neural networks and transfer learning
Jain, R., Nagrath, P., Kataria, G., Sirish Kaushik, V., & Jude Hemanth, D. (2020) · Measurement · doi:10.1016/j.measurement.2020.108046 · Cited by 325
Multimodal deep learning ensemble framework for skin cancer detection
Saeed, M. A., Afify, Y. M., Badr, N. L., & Helal, N. A. (2025) · Scientific Reports · doi:10.1038/s41598-025-30534-z · Cited by 7
Metadata
- Authors
- Jaiswal, A. K., Tiwari, P., Kumar, S., Gupta, D., Khanna, A., & Rodrigues, J. J. P. C.
- Venue
- Measurement
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 145
- Pages
- 511-518
- ISSN
- 0263-2241 (ISSN-L)
- OpenAlex
- W2948666538
- Cited by
- 507
- References
- 35
- FWCI
- 39.60
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jaiswal, A. K., Tiwari, P., Kumar, S., Gupta, D., Khanna, A., & Rodrigues, J. J. P. C. (2019). Identifying pneumonia in chest X-rays: A deep learning approach. Measurement. https://doi.org/10.1016/j.measurement.2019.05.076
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