Three-stage segmentation of lung region from CT images using deep neural networks

Autor: Michael Osadebey, Hilde K. Andersen, Dag Waaler, Kristian Fossaa, Anne C. T. Martinsen, Marius Pedersen

Publikováno v: BMC Medical Imaging, Vol 21, Iss 1, Pp 1-19 (2021)

Abstract Background Lung region segmentation is an important stage of automated image-based approaches for the diagnosis of respiratory diseases. Manual methods executed by experts are considered the gold standard, but it is time consuming and the ac

Externí odkaz: https://doaj.org/article/58bfb0e574104d8d94c8c18a2b15ad22

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Three-stage segmentation of lung region from CT images using deep neural networks

Autor: Dag Waaler, Hilde Kjernlie Andersen, Marius Pedersen, Michael Osadebey, Kristian Fossaa, Anne Catrine Trægde Martinsen

Publikováno v: BMC Medical Imaging
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-19 (2021)

Background Lung region segmentation is an important stage of automated image-based approaches for the diagnosis of respiratory diseases. Manual methods executed by experts are considered the gold standard, but it is time consuming and the accuracy is

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73791dd0b1b6dea80d5686bf11ee9f27
https://hdl.handle.net/11250/2785860

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Quantitative Evaluation and Comparison of Lung Contour Extraction Methods

Autor: Silva, José Silvestre, Silva, Augusto, Santos, Beatriz Sousa

Publikováno v: Eletrónica e Telecomunicações; Vol 3 No 2 (2000); 102-107
Eletrónica e Telecomunicações; vol. 3 n.º 2 (2000); 102-107
Electrónica e Telecomunicações; v. 3, n. 2 (2000); 102-107
1645-04
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
CIÊNCIAVITAE

Pulmonary contours in chest CT images areclosed curves that may, in some cases, exhibit multipleconcave and convex irregularities. In this paper we assess thequality of pulmonary contours obtained by several fullyautomated methods. A comparison among

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::23efa67e246d87b21a4a78b9239ff58a
https://hdl.handle.net/10316/13419