Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI

• Published in: Scientific reports Vol. 12; no. 1; pp. 10566 - 12
• Main Authors: Astley, Joshua R., Biancardi, Alberto M., Hughes, Paul J. C., Marshall, Helen, Smith, Laurie J., Collier, Guilhem J., Eaden, James A., Weatherley, Nicholas D., Hatton, Matthew Q., Wild, Jim M., Tahir, Bilal A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 22.06.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 692/699/1785; 692/700/1421/1628; Deep Learning; Experimental methods; Functional magnetic resonance imaging; Helium; Humanities and Social Sciences; Humans; Image processing; Lung - diagnostic imaging; Lung diseases; Lung Volume Measurements; Magnetic Resonance Imaging - methods; Male; Morbidity; multidisciplinary; Neural networks; Respiratory diseases; Science; Science (multidisciplinary); Segmentation; Spatial discrimination; Statistical analysis; Training; Ventilation; Xenon

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is an essential component of the diagnosis, treatment planning, monitoring, and treatment assessment of respiratory diseases. Insights into numerous pulmonary pathologies can be gleaned from functional lu...