Abstract
This paper introduces computational tools that could enable personalized, predictive, preemptive, and participatory (P4) Pulmonary medicine. We demonstrate approaches to (a) stratify lungs from different subjects based on the spatial distribution of parenchymal abnormality and (b) visualize the stratification through glyphs that convey both the grouping efficacy and an iconic overview of an individual’s lung wellness. Affinity propagation based on regional parenchymal abnormalities is used in the referenceless stratification. Abnormalities are computed using supervised classification based on Earth Mover’s distance. Twenty natural clusters were detected from 372 CT lung scans. The computed clusters correlated with clinical consensus of 9 disease types. The quality of inter- and intra-cluster stratification as assessed by ANOSIM R was 0.887 ± 0.18 (pval < 0.0005). The proposed tools could serve as biomarkers to objectively diagnose pathology, track progression and assess pharmacologic response within and across patients.
Chapter PDF
Similar content being viewed by others
References
De Craene, M., du Bois d’Aische, A., Macq, B., Warfield, S.K.: Multi-subject Registration for Unbiased Statistical Atlas Construction. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 655–662. Springer, Heidelberg (2004)
Srinivasan, R., Shriram, K.S., Suryanarayanan, S.: Unbiased Stratification of Left Ventricles. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 551–558. Springer, Heidelberg (2008)
Frey, B., Dueck, D.: Clustering by Passing Messages Between Data Points. Science 315, 972–976 (2007)
Akira, M., Inoue, Y., Kitaichi, M., Yamamoto, S., Arai, T., Toyokawa, K.: Usual Interstitial Pneumonia and Nonspecific Insterstitial Pneumonia with and without concurrent emphysema. Radiology 251, 271–279 (2009)
Ross, J.C., Estépar, R.S.J., Díaz, A., Westin, C.-F., Kikinis, R., Silverman, E.K., Washko, G.R.: Lung Extraction, Lobe Segmentation and Hierarchical Region Assessment for Quantitative Analysis on High Resolution Computed Tomography Images. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009. LNCS, vol. 5762, pp. 690–698. Springer, Heidelberg (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Raghunath, S., Rajagopalan, S., Karwoski, R.A., Bartholmai, B.J., Robb, R.A. (2011). Referenceless Stratification of Parenchymal Lung Abnormalities. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6893. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23626-6_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-23626-6_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23625-9
Online ISBN: 978-3-642-23626-6
eBook Packages: Computer ScienceComputer Science (R0)