INVERSE IMAGING OF THE BREAST WITH A MATERIAL CLASSIFICATION TECHNIQUE

In recent publications [Chew et al., IEEE Trans. Blomed. Eng, BME-9, 2 18-225 (1990); Borup et al., Ultrason. Imaging 14, 69-55 (1992)] the i nverse imaging problem has been solved by means of a two-step iterativ e method. In this paper, a third step is introduced for ultrasound ima ging of the breast. In this step, which is based on statistical patter n recognition, classification of tissue types and a priori knowledge o f the anatomy of the breast are integrated into the iterative method. Use of this material classification technique results in more rapid co nvergence to the inverse solution-approximately 40% fewer iterations a re required-as well as greater accuracy. In addition, tumors an detect ed early in the reconstruction process. Results for reconstructions of a simple two-dimensional model of the human breast are presented. The se reconstructions are extremely accurate when system noise and variat ions in tissue parameters an not too great. However, for the algorithm used, degradation of the reconstructions and divergence from the corr ect solution occur when system noise and variations in parameters exce ed threshold values. Even in this case, however, tumors are still iden tified within a few iterations. (C) 1998 Acoustical Society of America .