The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Deep-learning framework to detect lung abnormality – A study with chest X-Ray and lung CT scan images
Open accessAbstract
Abstract Lung abnormalities are highly risky conditions in humans. The early diagnosis of lung abnormalities is essential to reduce the risk by enabling quick and efficient treatment. This research work aims to propose a Deep-Learning (DL) framework to examine lung pneumonia and cancer. This work proposes two different DL techniques to assess the considered problem: (i) The initial DL method, named a modified AlexNet (MAN), is proposed to classify chest X-Ray images into normal and pneumonia class. In the MAN, the classification is implemented using with Support Vector Machine (SVM), and its performance is compared against Softmax. Further, its performance is validated with other pre-trained DL techniques, such as AlexNet, VGG16, VGG19 and ResNet50. (ii) The second DL work implements a fusion of handcrafted and learned features in the MAN to improve classification accuracy during lung cancer assessment. This work employs serial fusion and Principal Component Analysis (PCA) based features selection to enhance the feature vector. The performance of this DL frame work is tested using benchmark lung cancer CT images of LIDC-IDRI and classification accuracy (97.27%) is attained.
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Cites
Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., & Summers, R. M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.369 · Cited by 4,616
Zech, J. R., Badgeley, M. A., Liu, M., Costa, A. B., Titano, J. J., & Oermann, E. K. (2018) · PLOS Medicine · doi:10.1371/journal.pmed.1002683 · Cited by 1,719 · cited 1×
“Of these, an extensive quantity of traditional, modified form and customary DL architecture are already proposed and implemented to examine a class of clinical-grade and benchmark medical pictures [13-17].”
BackgroundRajpurkar, P., Irvin, J., Ball, R. L., Zhu, K., Yang, B., Mehta, H., Duan, T., Ding, D., Bagul, A., Langlotz, C. P., et al. (2018) · PLOS Medicine · doi:10.1371/journal.pmed.1002686 · Cited by 1,449
Cheng, J.-Z., Ni, D., Chou, Y.-H., Qin, J., Tiu, C.-M., Chang, Y.-C., Huang, C.-S., Shen, D., & Chen, C.-M. (2016) · Scientific Reports · doi:10.1038/srep24454 · Cited by 755
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
Irvin, J., Rajpurkar, P., Ko, M., Yu, Y., Ciurea-Ilcus, S., Chute, C., Marklund, H., Haghgoo, B., Ball, R., Shpanskaya, K., et al. (2019) · arXiv · doi:10.48550/arxiv.1901.07031 · Cited by 392
Cited by
Deep learning approaches for COVID-19 detection based on chest X-ray images
Ismael, A. M., & Şengür, A. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114054 · Cited by 746
Hybrid deep learning for detecting lung diseases from X-ray images
Bharati, S., Podder, P., & Mondal, M. R. H. (2020) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2020.100391 · Cited by 404
Ahmad, K., Maabreh, M., Ghaly, M., Khan, K., Qadir, J., & Al-Fuqaha, A. (2022) · Computer Science Review · doi:10.1016/j.cosrev.2021.100452 · Cited by 291
Pre-training in Medical Data: A Survey
Qiu, Y., Lin, F., Chen, W., & Xu, M. (2023) · Machine Intelligence Research · doi:10.1007/s11633-022-1382-8 · Cited by 30
Metadata
- Authors
- Bhandary, A., Prabhu, G. A., Rajinikanth, V., Thanaraj, K. P., Satapathy, S. C., Robbins, D. E., Shasky, C., Zhang, Y.-D., Tavares, J. M. R. S., & Raja, N. S. M.
- Venue
- Pattern Recognition Letters
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 129
- Pages
- 271-278
- ISSN
- 0167-8655 (ISSN-L)
- OpenAlex
- W2983132969
- Cited by
- 449
- References
- 5
- FWCI
- 31.20
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Bhandary, A., Prabhu, G. A., Rajinikanth, V., Thanaraj, K. P., Satapathy, S. C., Robbins, D. E., Shasky, C., Zhang, Y.-D., Tavares, J. M. R. S., & Raja, N. S. M. (2020). Deep-learning framework to detect lung abnormality – A study with chest X-Ray and lung CT scan images. Pattern Recognition Letters. https://doi.org/10.1016/j.patrec.2019.11.013
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