A radiomics approach for lung nodule detection in thoracic CT images based on the dynamic patterns of morphological variation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00330-021-08456-x.pdf
Reference60 articles.
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2. Pehrson LM, Nielsen MB, Ammitzbøl Lauridsen C (2019) Automatic pulmonary nodule detection applying deep learning or machine learning algorithms to the LIDC-IDRI database: a systematic review. Diagnostics (Basel) 9(1). doi: https://doi.org/10.3390/diagnostics9010029
3. Valente IR, Cortez PC, Neto EC et al (2016) Automatic 3D pulmonary nodule detection in CT images: a survey. Comput Methods Programs Biomed 124:91–107
4. Jacobs C, van Rikxoort EM, Twellmann T et al (2014) Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images. Med Image Anal 18:374–384
5. Shaukat F, Raja G, Gooya A et al (2017) Fully automatic detection of lung nodules in CT images using a hybrid feature set. Med Phys 44(7):3615–3629
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