Description generation of abnormal densities found in radiographs.
In this paper we present a system for describing renal stones found in radiographs. The system generates descriptions that adhere to those generated by radiologists. The descriptions are formulated by discovering the spatial relationships that exist between the major organs and the renal stones. The system consists of three major components. The first is the image processing component which is responsible for locating the stone. The second component is the inference network minimization component which determines which spatial relationships, of all those that exist between the stone and the organs, is the most descriptive. The third component is the natural language generation component which is responsible for translating the spatial relationships into appropriate medical terminology. We will illustrate all these components on several examples.
Abella
A
A
AT&T Bell Laboratories, Murray Hill, NJ, USA.
Kender
J R
JR
Starren
J
J
D000465:Algorithms; D006801:Humans; D007668:Kidney / Q000000981:diagnostic imaging; D007669:Kidney Calculi / Q000000981:diagnostic imaging*; D009323:Natural Language Processing; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted