title: Development of a personalized training system using the Lung Image Database Consortium and Image Database resource Initiative Database.
abstract: OBJECTIVE
  The aim of this study was to develop a personalized training system using the Lung Image Database Consortium (LIDC) and Image Database resource Initiative (IDRI) Database, because collecting, annotating, and marking a large number of appropriate computed tomography (CT) scans, and providing the capability of dynamically selecting suitable training cases based on the performance levels of trainees and the characteristics of cases are critical for developing a efficient training system.
  
  
  METHODS
  A novel approach is proposed to develop a personalized radiology training system for the interpretation of lung nodules in CT scans using the Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) database, which provides a Content-Boosted Collaborative Filtering (CBCF) algorithm for predicting the difficulty level of each case of each trainee when selecting suitable cases to meet individual needs, and a diagnostic simulation tool to enable trainees to analyze and diagnose lung nodules with the help of an image processing tool and a nodule retrieval tool.
  
  
  RESULTS
  Preliminary evaluation of the system shows that developing a personalized training system for interpretation of lung nodules is needed and useful to enhance the professional skills of trainees.
  
  
  CONCLUSIONS
  The approach of developing personalized training systems using the LIDC/IDRL database is a feasible solution to the challenges of constructing specific training program in terms of cost and training efficiency.
authors.affiliation: Key Laboratory for Embedded and Network Computing of Hunan Province, School of information science and engineering, Hunan University, 410082 Changsha, China. Electronic address: hllin@hnu.edu.cn.
authors.forename: Hongli
authors.initials: H
authors.lastname: Lin
authors.affiliation: Key Laboratory for Embedded and Network Computing of Hunan Province, School of information science and engineering, Hunan University, 410082 Changsha, China.
authors.forename: Weisheng
authors.initials: W
authors.lastname: Wang
authors.affiliation: Key Laboratory for Embedded and Network Computing of Hunan Province, School of information science and engineering, Hunan University, 410082 Changsha, China.
authors.forename: Jiawei
authors.initials: J
authors.lastname: Luo
authors.affiliation: Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada.
authors.forename: Xuedong
authors.initials: X
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D004503:Education, Medical, Graduate; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D011786:Quality Control; D011857:Radiographic Image Interpretation, Computer-Assisted; D013902:Radiography, Thoracic; D011871:Radiology / Q000193:education*; D014057:Tomography, X-Ray Computed
keywords: Content-Boosted Collaborative Filtering; LIDC/IDRI; Personalized radiology education; lung nodule