We are developing a computerized method for detection and characterization of interstitial diseases based on a quantitative analysis of geometric features of various infiltrate patterns in digital chest radiographs. In our approach, regions of interest (ROIs) with 128 × 128 matrix size (22.4 mm × 22.4 mm) are automatically selected, covering peripheral lung regions. Next, nodular and linear opacities, which are the basic components of interstitial infiltrates, are identified from two processed images obtained by use of a multiple-level thresholding technique and a line enhancement filter, respectively. Finally, the total area of nodular opacities and the total length of linear opacities in each ROI are determined as measures of geometric pattern features. We have applied this computer analysis to 72 ROIs with normal and abnormal patterns that were classified in advance by six chest radiologists. Preliminary results indicate that the distribution of measures of geometric-pattern features correlate well with radiologists' classification. These early results are encouraging, and further evaluation hopes to establish that this computerized method might prove useful to radiologists in their assessment of interstitial diseases.
All Science Journal Classification (ASJC) codes
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Computer Science Applications