Accurate segmentation of lung nodule with low contrast boundaries by least weight navigation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-14620-w.pdf
Reference36 articles.
1. Aresta G, Cunha A, Campilho A (2017) Detection of juxta-pleural lung nodules in computed tomography images. In: Proc. SPIE Med. Imag. Comput.-Aided Diagnosis Med. Imag., Orlando, FL, USA, vol. 10134, p. 101343N
2. Armato SG 3rd, McLennan G, Bidaut L et al (2011) The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys 38(2):915–931. https://doi.org/10.1118/1.3528204
3. Armato SG, Sensakovic WF (2004) Automated lung segmentation for thoracic CT: Impact on computer-aided diagnosis1. Acad Radiol 11(9):1011–1021
4. Armato SG, Altman MB, Rivière PJL (2003) Automated detection of lung nodules in CT scans: Effect of image reconstruction algorithm. Med Phys 30(3):461472
5. Brown MS et al (1997) Method for segmenting chest CT image data using an anatomical model: Preliminary results. IEEE Trans Med Imag 16(6):828–839
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