title: Risk Analysis for Pathological Changes in Pulmonary Parenchyma Based on Lung Computed Tomography Images.
abstract: OBJECTIVE
  The purpose of this study is to design a content-based medical image retrieval system, which helps excavate and assess pathological change of pulmonary parenchyma for risks analysis.
  
  
  METHODS
  A data set including lung computed tomography images obtained from 115 patients who experienced pathological changes in pulmonary parenchyma is used. Using morphological theory, images are preprocessed and decomposed into groups of pixel blocks (words), which construct vocabulary. A latent Dirichlet allocation (LDA) model is constructed to assess each image for risk analysis with the method of leave-one-out cross-validation. The precision and recall rate are used as the performance assessment criteria.
  
  
  RESULTS
  The LDA model generates a relevance rank of retrieval results from high to low. From the top 50 images, precision of identical tissue is 0.76 ± 0.031 and precision of each attribute of pulmonary parenchyma range from 0.776 ± 0.043 to 0.984 ± 0.008.
  
  
  CONCLUSIONS
  The study results demonstrate that the proposed LDA model is conductive to lung computed tomography image retrieval and has reliable efficacy on risk analysis about pathological changes of pulmonary parenchyma.
authors.affiliation: From the *Sino-Dutch Biomedical and Information Engineering School, Hunnan Campus, Northeastern University, Shenyang, China; and †College of Engineering, University of Texas at El Paso, El Paso, TX.
authors.forename: Hong Yang
authors.initials: HY
authors.lastname: Jiang
authors.forename: He
authors.initials: H
authors.lastname: Ma
authors.forename: Wei
authors.initials: W
authors.lastname: Qian
authors.forename: Guo Hui
authors.initials: GH
authors.lastname: Wei
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D057225:Data Mining; D020000:Decision Support Systems, Clinical / Q000458:organization & administration; D005260:Female; D006801:Humans; D007089:Image Enhancement; D008168:Lung / Q000000981:diagnostic imaging* / Q000473:pathology; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D000072356:Parenchymal Tissue / Q000000981:diagnostic imaging* / Q000473:pathology; D011857:Radiographic Image Interpretation, Computer-Assisted; D011873:Radiology Information Systems / Q000458:organization & administration*; D015203:Reproducibility of Results; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed