Application of image analysis techniques to distinguish benign from malignant solitary pulmonary nodules imaged on CT

Michael F. McNitt-Gray, Eric M. Hart, Nathaniel Wyckoff, James W. Sayre, Jonathan G. Goldin, Denise R. Aberle

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


The purpose of this research is to characterize solitary pulmonary nodules as benign or malignant based on quantitative measures extracted from high resolution CT images. High resolution CT images of 17 patients with solitary pulmonary nodules and definitive diagnoses were obtained. The diagnoses of these 17 cases (11 benign and 6 malignant) were determined from either radiologic follow-up or pathological specimens. On the HRCT images, solitary nodules were identified using semiautomated contouring techniques. From the resulting contours, several quantitative measures are extracted related to the nodule's size, shape, density and texture. A stepwise discriminant analysis was performed to determine which combination of measures are best able to discriminate between the benign and malignant nodules. Using several selected features, a linear discriminant analysis was performed on the 17 cases. The preliminary discriminant analysis identified two different texture measures as the top features in discriminating between benign and malignant nodules. The linear discriminant analysis using these features correctly classified 16/17 cases (94.1%) of the training set. A less biased estimate, using jackknifed training and testing yielded 15/17 cases (88.2%) correctly classified. The preliminary results of this approach are very promising in characterizing solitary nodules using quantitative measures extracted from HRCT images.

Original languageEnglish (US)
Pages (from-to)1225-1233
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Dec 1 1998
EventMedical Imaging 1998: Image Processing - San Diego, CA, United States
Duration: Feb 23 1998Feb 23 1998

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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