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J. Thiesse, J. M. Reinhardt, J. de Ryk, J. Leinen, W. Recheis, E. A. Hoffman, and G. McLennan. Three-dimensional visual truth of the normal airway tree for use as a quantitative comparison to micro-CT reconstructions. In A. Amini and A. Manduca, eds., Proc. SPIE Conf. Medical Imaging, vol. 5746, pp. 369-383, San Diego, CA, 2005.

Abstract: Mouse models are important for pulmonary research to gain insight into structure and function in normal and diseased states, thereby extending knowledge of human disease conditions. The flexibility of human disease induction into mice, due to their similar genome, along with their short gestation cycle makes mouse models highly suitable as investigative tools. Advancements in non-invasive imaging technology, with the development of micro-computed tomography (micro-CT), have aided representation of disease states in these small pulmonary system models. The generation of micro-CT 3D airway reconstructions has to date provided a means to examine structural changes associated with disease. The degree of accuracy of micro-CT is uncertain. Consequently, the reliability of quantitative measurements is questionable. We have developed a method of sectioning and imaging the whole mouse lung using the Large Image Microscope Array (LIMA) as the gold standard for comparison. Fixed normal mouse lungs were embedded in agarose and 250 micron sections of tissue were removed while the remaining tissue block was imaged with a stereomicroscope. A complete dataset of the mouse lung was acquired in this fashion. Following planar image registration, seeded region growing was used to segment the airways in each image. An algorithm was then created to stack the segmented images into a 3D array and render the 3D-isosurface. The resulting 3D model of the normal mouse airway tree developed from pathology images was then quantitatively assessed and used as the standard to compare the accuracy of structural measurements obtained from micro-CT.

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Keywords: airways measurement segmentation

Other publications by: J. Thiesse, J. M. Reinhardt, J. de Ryk, J. Leinen, W. Recheis, E. A. Hoffman, G. McLennan

Related journal papers:

J. M. Reinhardt, N. D. D'Souza, and E. A. Hoffman. Accurate Measurement of Intra-Thoracic Airways. IEEE Trans. Medical Imaging, vol. 16, no. 6, pp. 820-827, 1997. (details)
D. Aykac, E. A. Hoffman, G. McLennan, and J. M. Reinhardt. Segmentation and analysis of the human airway tree from three-dimensional X-Ray CT images. IEEE Trans. Medical Imaging, vol. 22, no. 8, pp. 940-950, 2003. (details)
O. Saba, E. A. Hoffman, and J. M. Reinhardt. Maximizing Quantitative Accuracy of Lung Airway Lumen and Wall Measures Obtained from X-ray CT Imaging. J. Applied Physiology, vol. 95, pp. 1063-1095, 2003. (details)
T. E. Robinson, F. R. Long, P. Raman, P. Saha, M. J. Edmond, J. M. Reinhardt, R. Raman, and A. S. Brody. An airway phantom to standardize CT acquisition in multi-center clinical trials. Acad. Radiol., vol. 16, no. 9, pp. 1134-1141, 2009. (details)
J. M. Reinhardt and W. E. Higgins. Paradigm for Shape-Based Image Analysis. Optical Engineering, vol. 37, no. 2, pp. 570-581, 1998. (details)

Related conference papers:

R. A. Chiplunkar, J. M. Reinhardt, and E. A. Hoffman. Segmentation and Quantification of the Primary Human Airway Tree from 3-D X-ray CT. In E. A. Hoffman, ed., Proc. SPIE Conf. Medical Imaging, vol. 3033, pp. 403-414, Newport Beach, CA, 1997. (details)
N. D. D'Souza, J. M. Reinhardt, and E. A. Hoffman. ASAP: Interactive Quantification of 2D Airway Geometry. In E. A. Hoffman, ed., Proc. SPIE Conf. Medical Imaging, vol. 2709, pp. 180-196, Newport Beach, CA, 1996. (details)
J. M. Reinhardt, S. A. Raab, N. D. D'Souza, and E. A. Hoffman. Intra-thoracic airway measurement: Ex vivo validation. In E. A. Hoffman, ed., Proc. SPIE Conf. Medical Imaging, vol. 3033, pp. 69-80, Newport Beach, CA, 1997. (details)
J. M. Reinhardt, W. Park, E. A. Hoffman, and M. Sonka. Intrathoracic airway wall detection using graph search with CT scanner PSF information. In E. A. Hoffman, ed., Proc. SPIE Conf. Medical Imaging, vol. 3033, pp. 93-101, Newport Beach, CA, 1997. (details)
O. Saba, E. A. Hoffman, and J. M. Reinhardt. Computed tomographic-based estimation of airway size with correction for scanned plane tilt angle. In C.-T. Chen and A. V. Clough, eds., Proc. SPIE Conf. Medical Imaging, vol. 3978, pp. 58-66, San Diego, CA, 2000. (details)

Related theses:

D. Aykac. Segmentation and analysis of the human airway tree from 3D X-ray CT images. MS thesis, The University of Iowa, Iowa City, IA, 2000. (details)
O. Saba. Accurate estimation of airway geometry with tilt angle estimation from 2D HRCT slices. MS thesis, The University of Iowa, Iowa City, IA, 2000. (details)
D. Gopalakrishnan. Color analysis of the human airway wall. MS thesis, The University of Iowa, Iowa City, IA, 2003. (details)
S. Ukil. Anatomy-guided lung lobe segmentation and fissure analysis in X-ray CT images. PhD thesis, The University of Iowa, Iowa City, IA, 2006. (details)
L. Zhang. Atlas-driven lung lobe segmentation in volumetric X-ray CT images. PhD thesis, The University of Iowa, Iowa City, IA, 2002. (details)