Handwritten laboratory test order form recognition module for distributed clinic

• Autorzy: Sas J.
• Języki publikacji: EN

Abstrakty

EN

The work describes methods used in a laboratory order form recognition module of a hospital information system. Three-level form analysis architecture is proposed. The lower alphabetical level is responsible for separate character recognition. On the intermediate level, recognised strings are verified against the lexicons of items specific for a particular form field. Probabilistic model is used to select the set of most probable items. On the upper level, the dependencies between the form data items are taken into account to further improve the recognition performance. The presented approach was implemented in the medical information system supporting clinic laboratory operation. The laboratory test orders prepared manually by the physician in the paper form, in the net of distributed outpatient clinics are processed in the central hospital laboratory. In the central laboratory the paper forms are scanned, recognised and entered into the information system. The performance tests results are discussed and some further improvements of the applied recognition method are also suggested in the paper.

Słowa kluczowe

EN

intelligent character recognition; pattern recognition; hospital information systems

PL

inteligentne rozpoznawanie znaków; rozpoznawanie wzorców; szpitalne systemy informatyczne

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2004
• Tom: Vol. 8
• Strony: MM59--68
• Opis fizyczny: Bibliogr. 7 poz., rys., tab.

Twórcy

autor

Sas J.

• Computer Science Department, Wroclaw University of Technology, 50-370 Wrocław, Wyb. Wyspiańskiego 27

Bibliografia

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• [2] KURZYŃSKI M., Pattern Recognition. Statistical Methods. Techn. Univ. of Wroclaw Press, Wrocław, 1997
• [3] LIU Z.Q., CAI J., BUSE R., Handwriting Recognition. Soft Computing and Probabilistic Approaches, Springer, Berlin, Heidelberg, New York 2003
• [4] LIU C., NAKASHIMA K., SAKO H., FUJISAWA H., Handwritten Digit Recognition: benchmarking of state-of-the-art techniques, Pattern Recognition, No. 36, 2003
• [5] PLAMONDON R., SRIHARI S., On-line and Off-line Handwriting Recognition: A Comprehensive Survey. IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 22, No. 1, Jan. 2000
• [6] TRĄBKA W., Hospital Information Systems, University Press "Vesalius", Kraków 1999
• [7] UCHIDA S., SAKOE H., Eigen-deformations for elastic matching based handwritten character recognition. Pattern Recognition No 36, 2003