Border to border distance based lung parenchyma segmentation including juxta-pleural nodules
Pages 10421 - 10443
Abstract
Lung Segmentation is one of the pre-processing steps for lung cancer diagnosis. Segmentation of lung contour is challenging when the nodules are attached to the surrounding tissues of the lung, such as juxta-pleural boundary or vasculature. This paper proposes a lung parenchyma segmentation framework based on multiple image frames with novel approaches for juxta-pleural nodule identification and lung contour correction. The juxta-pleural nodule identification works by computing the distance between the lung borders on adjacent slices. These approaches extract the lung boundary of current and previous slices and calculate the shortest distance between the two boundary contour points to detect the nodule candidates and correct the nodule boundary. These approaches were experimented on at least 11 thoracic image volumes with juxta-pleural nodules from the LIDC-IDRI dataset and achieved an average volumetric overlap fraction of 98.59%. Compared with the other state-of-the-art methods, the proposed method is simple and very efficient for segmenting the lung parenchyma while including the juxta-pleural nodules.
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- Border to border distance based lung parenchyma segmentation including juxta-pleural nodules
Index terms have been assigned to the content through auto-classification.
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© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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Kluwer Academic Publishers
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Publication History
Published: 31 August 2022
Accepted: 02 August 2022
Revision received: 25 June 2022
Received: 30 April 2021
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- Department of Science and Technology, Ministry of Science and Technology (IN)
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