论文信息 - Automated Recognition of Lateral from PA Chest Radiographs: Saving Seconds in a PACS Environment

Automated Recognition of Lateral from PA Chest Radiographs: Saving Seconds in a PACS Environment

Images acquired in a two-view digital chest examination are frequently not electronically distinguishable. As a result the lateral and posterioanterio (PA) images are often improperly positioned on a PACS work station. A series of 1998 chest radiographs (999 lateral, 999 PA or AP) were used to develop a neural network classifier. The images were down-sampled to 16 × 16 matrices, and a feed-forward neural network was trained and tested using the “leave-one-out” method. Using five nodes in the hidden layer, the neural network correctly identified 987 of the 999 test cases (98.8%) (average of six runs). The simple architecture and speed of this technique suggests that it would be a useful addition to PACS work station software. The accumulated time saved by correctly positioning the lateral and PA chest images on the work station monitors in accordance with each radiologist’s hanging protocols was estimated to be about 1 week of radiologist time per year.

John M. Boone | J. Anthony Seibert | Greg S. Hurlock | Richard L. Kennedy

[1] H. Kato. Computed Radiography , 1989, [1989] Proceedings. The First International Conference on Image Management and Communication in Patient Care: Implementation and Impact.

[2] Tomonori Gido,et al. Improved computed radiography image quality from a BaFl:Eu photostimulable phosphor plate. , 2002, Medical physics.

[3] J. Boone. Sidetracked at the crossroads. , 1994, Radiology.

[4] J M Boone,et al. Neural networks in radiologic diagnosis. I. Introduction and illustration. , 1990, Investigative radiology.

[5] M Freedman. Chest image quality: film-screen vs. computed radiography. , 1991, Administrative radiology : AR.

[6] J M Boone,et al. Neural networks in radiology: an introduction and evaluation in a signal detection task. , 1990, Medical physics.

[7] K. Doi,et al. Computer-aided diagnostic scheme for lung nodule detection in digital chest radiographs by use of a multiple-template matching technique. , 2001, Medical physics.

[8] Robert M. Nishikawa,et al. Computer aided diagnosis of breast cancer on mammograms , 1997, Breast cancer.

[9] K. Doi,et al. Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images. , 2002, Medical physics.

[10] G. W. Gross,et al. Neural networks in radiologic diagnosis. II. Interpretation of neonatal chest radiographs. , 1990, Investigative radiology.