Conference proceeding
Three-dimensional histopathology of lung cancer with multimodality image registration
Proceedings of SPIE, Vol.6512(1), pp.65122F-65122F-8
Medical Imaging 2007: Image Processing
03/08/2007
DOI: 10.1117/12.710597
Abstract
Identifying the three-dimensional content of non-small cell lung cancer tumors is a vital step in the pursuit of understanding cancer growth, development and response to treatment. The majority of non-small cell lung cancer tumors are histologically heterogeneous, and consist of the malignant tumor cells, necrotic tumor cells, fibroblastic stromal tissue, and inflammation. Geometric and tissue density heterogeneity are utilized in computed tomography (CT) representations of lung tumors for distinguishing between malignant and benign nodules. However, the correlation between radiolographical heterogeneity and corresponding histological content has been limited. In this study, a multimodality dataset of human lung cancer is established, enabling the direct comparison between histologically identified tissue content and micro-CT representation. Registration of these two datasets is achieved through the incorporation of a large scale, serial microscopy dataset. This dataset serves as the basis for the rigid and non-rigid registrations required to align the radiological and histological data. The resulting comprehensive, three-dimensional dataset includes radio-density, color and cellular content of a given lung tumor. Using the registered datasets, neural network classification is applied to determine a statistical separation between cancerous and non-cancerous tumor regions in micro-CT.
Details
- Title: Subtitle
- Three-dimensional histopathology of lung cancer with multimodality image registration
- Creators
- Jessica de Ryk - University of IowaJamie Weydert - University of IowaGary Christensen - University of IowaJacqueline Thiesse - University of IowaEman Namati - University of IowaJoseph Reinhardt - University of IowaEric Hoffman - University of IowaGeoffrey McLennan - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.6512(1), pp.65122F-65122F-8
- Conference
- Medical Imaging 2007: Image Processing
- DOI
- 10.1117/12.710597
- ISSN
- 0277-786X
- Language
- English
- Date published
- 03/08/2007
- Academic Unit
- Electrical and Computer Engineering; Roy J. Carver Department of Biomedical Engineering; Radiology; Radiation Oncology; Radiation Research Laboratory; The Iowa Institute for Biomedical Imaging; Advanced Pulmonary Physiomic Imaging Laboratory; Holden Comprehensive Cancer Center; Internal Medicine
- Record Identifier
- 9984197120302771
Metrics
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