DocumentCode :
2567797
Title :
Conformal mapping of nuclei in 3D tomographic cell images to assess shape heterogeneity
Author :
Nandakumar, Vivek ; An, Xing ; Wang, Yalin ; Johnson, Roger ; Meldrum, Deirdre
Author_Institution :
Sch. of Electr., Comput., & Energy Eng., Arizona State Univ., Tempe, AZ, USA
fYear :
2012
fDate :
2-5 May 2012
Firstpage :
222
Lastpage :
225
Abstract :
Nuclear shape and its heterogeneity are diagnostically important criteria used by pathologists in cancer diagnosis. Pathology assessment is currently qualitative and is based on 2D brightfield microscopy images. We propose an imaging informatics framework to quantify nuclear pleomorphism by statistical characterization of 3D nuclear shape. We applied optical projection tomographic microscopy (OPTM) to image individual hematoxylin and eosin-stained cells with isotropic, sub-micron spatial resolution. We used adaptive thresholding schemes to segment cells and nuclei, and applied spherical conformal mapping methods on the 3D nuclear masks to compute 256 rotation invariant coefficients as shape descriptors for each nucleus. As a first application, we tested our methods on normal and cancerous epithelial cell lines derived from human esophagus and breast, analyzing 10 cell images per class. We applied ANOVA techniques to assess variations in nuclear shape within each cell type and among the four cell types. The automated segmentation was 96% accurate compared to manual tracing of the volumes of interest. Statistical analysis of shape coefficients revealed that cancer cell nuclei from both organs exhibited considerably larger variance in their coefficients relative to the corresponding normal cell nuclei. Our results demonstrate the promise of our methodology for the development of quantitative pathological assessments.
Keywords :
biological organs; biomedical optical imaging; cancer; cellular biophysics; image resolution; image segmentation; mammography; medical image processing; optical tomography; statistical analysis; 2D brightfield microscopy; 3D nuclear shape; 3D tomographic cell images; ANOVA technique; OPTM; adaptive thresholding schemes; applied spherical conformal mapping; breast; cancer cell nuclei; cancer diagnosis; eosin-stained cells; epithelial cell lines; esophagus; hematoxylin; image segmentation; imaging informatics framework; nuclear pleomorphism; optical projection tomographic microscopy; pathology assessment; rotation invariant coefficient; shape descriptor; shape heterogeneity; spatial resolution; Cancer; Computer architecture; Conformal mapping; Image segmentation; Imaging; Microprocessors; Shape; 3D cell imaging; cancer; computed tomography; conformal mapping; heterogeneity; shape analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on
Conference_Location :
Barcelona
ISSN :
1945-7928
Print_ISBN :
978-1-4577-1857-1
Type :
conf
DOI :
10.1109/ISBI.2012.6235524
Filename :
6235524
Link To Document :
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