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Fat quantification and analysis of lung transplant patients on unenhanced chest CT images based on standardized anatomic space., , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 9788 of SPIE Proceedings, page 978817. SPIE, (2016)Control of Confounding and Reporting of Results in Causal Inference Studies. Guidance for Authors from Editors of Respiratory, Sleep, and Critical Care Journals., , , , , , , , , and 38 other author(s). Annals of the American Thoracic Society, 16 (1): 22-28 (January 2019)Causalitat; Confounding; Introductori<br/><br/>Bona Figura i recursos.Quantitative analysis of adipose tissue on chest CT to predict primary graft dysfunction in lung transplant recipients: a novel optimal biomarker approach., , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10575 of SPIE Proceedings, page 105753K. SPIE, (2018)Localization and segmentation of optimal slices for chest fat quantification in CT via deep learning., , , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 11317 of SPIE Proceedings, page 113170K. SPIE, (2020)Fat segmentation on chest CT images via fuzzy models., , , , , , , and . Medical Imaging: Image-Guided Procedures, volume 9786 of SPIE Proceedings, page 978609. SPIE, (2016)