title: A sparse representation based method to classify pulmonary patterns of diffuse lung diseases.
abstract: We applied and optimized the sparse representation (SR) approaches in the computer-aided diagnosis (CAD) to classify normal tissues and five kinds of diffuse lung disease (DLD) patterns: consolidation, ground-glass opacity, honeycombing, emphysema, and nodule. By using the K-SVD which is based on the singular value decomposition (SVD) and orthogonal matching pursuit (OMP), it can achieve a satisfied recognition rate, but too much time was spent in the experiment. To reduce the runtime of the method, the K-Means algorithm was substituted for the K-SVD, and the OMP was simplified by searching the desired atoms at one time (OMP1). We proposed three SR based methods for evaluation: SR1 (K-SVD+OMP), SR2 (K-Means+OMP), and SR3 (K-Means+OMP1). 1161 volumes of interest (VOIs) were used to optimize the parameters and train each method, and 1049 VOIs were adopted to evaluate the performances of the methods. The SR based methods were powerful to recognize the DLD patterns (SR1: 96.1%, SR2: 95.6%, SR3: 96.4%) and significantly better than the baseline methods. Furthermore, when the K-Means and OMP1 were applied, the runtime of the SR based methods can be reduced by 98.2% and 55.2%, respectively. Therefore, we thought that the method using the K-Means and OMP1 (SR3) was efficient for the CAD of the DLDs.
authors.affiliation: Medical Engineering Science, Graduate School of Medicine, Yamaguchi University, Ube 755-8611, Japan.
authors.forename: Wei
authors.identifier: 0000-0001-5081-7025
authors.initials: W
authors.lastname: Zhao
authors.affiliation: Global Innovation Research Organization, Ritsumeikan University, Kusatsu 525-8577, Japan.
authors.forename: Rui
authors.initials: R
authors.lastname: Xu
authors.affiliation: Medical Engineering Science, Graduate School of Medicine, Yamaguchi University, Ube 755-8611, Japan.
authors.forename: Yasushi
authors.identifier: 0000-0001-9707-4222
authors.initials: Y
authors.lastname: Hirano
authors.affiliation: National Institute of Technology, Oshima College, Oshima 742-2193, Japan.
authors.forename: Rie
authors.initials: R
authors.lastname: Tachibana
authors.affiliation: Medical Engineering Science, Graduate School of Medicine, Yamaguchi University, Ube 755-8611, Japan.
authors.forename: Shoji
authors.initials: S
authors.lastname: Kido
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008168:Lung / Q000000981:diagnostic imaging / Q000473:pathology / Q000502:physiology*; D008171:Lung Diseases / Q000145:classification* / Q000175:diagnosis*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D011381:Programming Languages; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed
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