Deconvolution Reconstruction of Thermoacoustic Imaging for Small-scale Objects / 航天医学与医学工程

ABSTRACT

Objective To increase the speed of thermoacoustic imaging, a deconvolution reconstruction (DR) algorithm is proposed for small-scale need detecting living beings, on the basis of deconvolution of thermoacustic imaging algorithm. Methods A new function was firstly constructed from the detected acoustic pressure function. Then, the distribution of electromagnetic wave absorption coefficient of the need detecting living beings could be reconstructed from this new function based on the deconvolution method. Computer simulation studies were carried out to compare the DR algorithm with the two popular algorithms the time-domain reconstruction (TDR) and the filtered back projection (FBP). Results For small-scale need detecting living beings, the accuracy of DR was nearly equivalent to TDR and slightly better than FBP. However, DR was about 4 to 6 times faster than TDR and about 25 to 100 times faster than FBP under the simulation experiment condition. Conclusion DR is a fast and effective algorithm of thermoacoustic imaging for small-scale living beings.