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Automatic Structuring of Radiology Free-Text Reports1

Ricky K. Taira, PhD, Stephen G. Soderland, PhD and Rex M. Jakobovits, PhD

1 From the Department of Radiology, Children's Hospital and Regional Medical Center, 4800 Sandpoint Way NE, Mailstop CH-69, Seattle, WA 98105 (R.K.T.); and the Department of Radiological Sciences, University of California, Los Angeles (S.G.S., R.M.J.). Presented as an infoRAD exhibit at the 1999 RSNA scientific assembly. Received March 24, 2000; revision requested May 1 and received June 1; accepted June 13. Supported in part by National Institutes of Health Grant No. P01-CA51198. Address correspondence to R.K.T. (e-mail: rtaira@u.washington.edu).



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  		Figure 1.   Output knowledge frame for the sample sentence, "A mass is seen in the right lower lobe that measures 5 cm in maximum diameter and is unchanged from the previous examination." Values from a controlled vocabulary are shown in capital letters, and values as expressed in the input text are enclosed in single quotation marks.

 


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  		Figure 2.   Diagram illustrates the processing architecture of our natural language processing system.

 


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  		Figure 3.   Dependency diagram generated by the parser shows modifier-head relations between words. The tail of an arc represents the modifier, whereas the tip represents the head.

 


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  		Figure 4.   The semantic interpreter derives the logical relations based on the parser-generated dependency diagram (cf Fig 3). The links between concepts 3, 4, and 7 indicate the logical relation "has-location." The arguments (ie, head, relationship between head and value, and modifying value) are "mass," "in," and "apex," respectively.

 


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  		Figure 5.   Screen shows a sample frame output (right) with intermediate parser results (left).

 




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