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

Sushravya Raghunath, Srinivasan Rajagopalan, Ronald A. Karwoski, Alan G. Larson, Brian Jack Bartholmai, Richard A. Robb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.

Original languageEnglish (US)
Title of host publicationStudies in Health Technology and Informatics
Pages362-368
Number of pages7
Volume173
DOIs
StatePublished - 2012
EventMedicine Meets Virtual Reality 19: NextMed, MMVR 2012 - Newport Beach, CA, United States
Duration: Feb 9 2012Feb 11 2012

Other

OtherMedicine Meets Virtual Reality 19: NextMed, MMVR 2012
CountryUnited States
CityNewport Beach, CA
Period2/9/122/11/12

Fingerprint

Macros
Navigation
Visualization
Lung
Pulmonary diseases
Observer Variation
Biopsy
Pathology
Bioinformatics
Tissue
Imaging techniques
Wetlands
Computational Biology
Lung Diseases
Cues
Technology
Therapeutics

Keywords

  • Detail-on-demand visualization
  • Glyphs
  • Lung visualization
  • Maximum feature projection
  • Parenchymal abnormalities

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Raghunath, S., Rajagopalan, S., Karwoski, R. A., Larson, A. G., Bartholmai, B. J., & Robb, R. A. (2012). Detail-on-demand visualization for lean understanding of lung abnormalities. In Studies in Health Technology and Informatics (Vol. 173, pp. 362-368) https://doi.org/10.3233/978-1-61499-022-2-362

Detail-on-demand visualization for lean understanding of lung abnormalities. / Raghunath, Sushravya; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Larson, Alan G.; Bartholmai, Brian Jack; Robb, Richard A.

Studies in Health Technology and Informatics. Vol. 173 2012. p. 362-368.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Raghunath, S, Rajagopalan, S, Karwoski, RA, Larson, AG, Bartholmai, BJ & Robb, RA 2012, Detail-on-demand visualization for lean understanding of lung abnormalities. in Studies in Health Technology and Informatics. vol. 173, pp. 362-368, Medicine Meets Virtual Reality 19: NextMed, MMVR 2012, Newport Beach, CA, United States, 2/9/12. https://doi.org/10.3233/978-1-61499-022-2-362
Raghunath S, Rajagopalan S, Karwoski RA, Larson AG, Bartholmai BJ, Robb RA. Detail-on-demand visualization for lean understanding of lung abnormalities. In Studies in Health Technology and Informatics. Vol. 173. 2012. p. 362-368 https://doi.org/10.3233/978-1-61499-022-2-362
Raghunath, Sushravya ; Rajagopalan, Srinivasan ; Karwoski, Ronald A. ; Larson, Alan G. ; Bartholmai, Brian Jack ; Robb, Richard A. / Detail-on-demand visualization for lean understanding of lung abnormalities. Studies in Health Technology and Informatics. Vol. 173 2012. pp. 362-368
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