Cargando…
CT texture analysis of histologically proven benign and malignant lung lesions
The purpose of our study was to determine accuracy of CT texture analysis (CTTA) for differentiating benign from malignant pulmonary nodules, and well-differentiated from poorly differentiated lung cancers, with histology as the standard of reference. In this IRB-approved study, 175 adult patients (...
Autores principales: | Digumarthy, Subba R., Padole, Atul M., Gullo, Roberto Lo, Singh, Ramandeep, Shepard, Jo-Anne O., Kalra, Mannudeep K. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039644/ https://www.ncbi.nlm.nih.gov/pubmed/29952966 http://dx.doi.org/10.1097/MD.0000000000011172 |
Ejemplares similares
-
Can CT radiomic analysis in NSCLC predict histology and EGFR mutation status?
por: Digumarthy, Subba R., et al.
Publicado: (2019) -
Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
por: Digumarthy, Subba R., et al.
Publicado: (2019) -
Radiomic features of primary tumor by lung cancer stage: analysis in BRAF mutated non-small cell lung cancer
por: Padole, Atul, et al.
Publicado: (2020) -
Is Weight-Based Adjustment of Automatic Exposure Control Necessary for the Reduction of Chest CT Radiation Dose?
por: Prakash, Priyanka, et al.
Publicado: (2010) -
Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs
por: Yoo, Hyunsuk, et al.
Publicado: (2020)