Detail-on-demand visualization for lean understanding of lung abnormalities

In some respects, the lung is an anatomical bog - having limited referential landmarks. Nonetheless, precise understanding of the abnormalities that inflict this organ is crucial to effective clinical diagnosis and treatment. However, wading interactively through a three-dimensional scan of the lung poses a visual quagmire to the radiologist, resulting in significant interpretive differences due to inter and intra observer variation. Despite the continuing progress in quantitative imaging, lack of unambiguous visualization with accurately, relevant cues severely hinders the clinical adoption of many computational tools. We address this unmet need through a lean visualization paradigm wherein information is presented hierarchically to provide an interactive macro-to-micro view of lung pathologies. At the macro level, the structural and functional information is summarized into a synoptic glyph that is readily interpreted and correlated to a priori known disease states. The glyphs are "patho-spatio-temporally" tagged to facilitate navigation through the level-of-detail scales, down to the micro level values in the image voxels, providing quantitative interpretation of tissue type and the confidence level in the quantitation. A novel volume compositing scheme is proposed to specify and guide to the optimal site for surgical lung biopsy. This intuitive, interactive interface for rapid and unambiguous navigation towards the clinical endpoint harnesses the power of bio-informatics technology to provide an efficient, clinically relevant and comprehensive summary of pulmonary disease, including precise location, spatial extent and intrinsic character.