nach oben

Erschienen in:

2022 | OriginalPaper | Buchkapitel

Weighted Box Fusion Ensembling for Lung Disease Detection

verfasst von : Huy Tran, Long TonThat, Kien Trang

Erschienen in: 8th International Conference on the Development of Biomedical Engineering in Vietnam

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Lung disease is a kind of infection that cannot be observed by human eyes, but it can be detected by X-ray images. Nevertheless, diagnostic accuracy from the look on these X-ray images is always a challenging task because it frequently relies on the experiences of the doctors. Hence, many computer vision techniques are developed to support medical staffs to perform lung disease detection. So as to encourage different detectors to identify different kinds of lung disease, this paper proposes a novel post-processing technique, a Weighted Box Fusion (WBF) ensembling algorithm, which may improve the efficiency in lung disease detection. This algorithm is applied to an available benchmarking dataset of X-ray chest in literature for justifying its performance.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Visual Object Tracking Method of Spatio-temporal Context Learning with Scale Variation

Nächstes Kapitel Epileptic Seizure Detection Based on Electroencephalography Signals and One-Dimensional Convolutional Neural Network

Centers for Disease Control and Prevention. https://www.cdc.gov/dotw/pneumonia/

Rajpurkar P, Irvin J, Zhu K, Yang B, Mehta H, Duan T, Ding D, Bagul A, Langlotz C, Shpanskaya K, Lungren MP (2017) Radiologist‐level pneumonia detection on chest X‐rays with deep learning. arXiv preprint arXiv:1711.05225

Lakhani P, Sundaram B (2017) Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks. Radiology 284(2):574–582CrossRef

Huang G, Liu Z, Van Der Maaten L, Weinberger KQ (2017) Densely connected convolutional networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4700–4708

Islam MT, Aowal MA, Minhaz AT, Ashraf K (2017) Abnormality detection and localization in chest X-rays using deep convolutional neural networks. Computer Science, Cornell University, arXiv:1705.09850v3 [cs.CV]

Yao L, Poblenz E, Dagunts D, Covington B, Bernard D, Lyman K (2017) Learning to diagnose from scratch by exploiting dependencies among labels. Computer Science, Cornell University, arXiv:1710.10501v2 [cs.CV]

Li Z, Wang C, Han M, Xue Y, Wei W, Li LJ, Fei-Fei L (2018) Thoracic disease identification and localization with limited supervision. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 8290–8299

Cai J, Lu L, Harrison AP, Shi X, Chen P, Yang L (2018) Iterative attention mining for weakly supervised thoracic disease pattern localization in chest X-rays. In: International conference on medical image computing and computer-assisted intervention. Springer, Cham, pp 589–598

Solovyev R, Wang W (2019) Weighted boxes fusion: ensembling boxes for object detection models. Image Vis Comput 107, Article 104117

10.

Bodla N, Singh B, Chellappa R, Davis LS (2017) Soft-NMS—improving object detection with one line of code. In: Proceedings of the IEEE international conference on computer vision, pp 5561–5569

11.

Wang X, Peng Y, Lu L, Lu Z, Bagheri M, Summers RM (2017) ChestX-ray8: hospital-scale chest X-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2097–2106

12.

Zhou B, Khosla A, Lapedriza A, Oliva A, Torralba A (2016) Learning deep features for discriminative localization. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2921–2929

13.

Paszke A, Gross S, Massa F, Lerer A, Bradbury J, Chanan G, Killeen T, Lin Z, Gimelshein N, Antiga L, Desmaison A (2019) PyTorch: an imperative style, high-performance deep learning library. In: Advances in neural information processing systems, pp 8024–8035

14.

Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. 3rd International Conference on Learning Representations (ICLR) (Poster section), arXiv:1412.6980v9 [cs.LG]

15.

Zhou H, Li Z, Ning C, Tang J (2017) CAD: Scale invariant framework for real-time object detection. In: Proceedings of the IEEE international conference on computer vision workshops, pp 760–68

Titel: Weighted Box Fusion Ensembling for Lung Disease Detection
verfasst von: Huy Tran
Long TonThat
Kien Trang
Verlag: Springer International Publishing
Buch: 8th International Conference on the Development of Biomedical Engineering in Vietnam
Print ISBN: 978-3-030-75505-8

Electronic ISBN: 978-3-030-75506-5

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-3-030-75506-5_60

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner