Research On Image Quality Improvement For Photoacoustic Tomography Based On Spatially Variation Deconvolution

Photoacoustic computed tomography(PACT)is a novel,noninvasive biomedical imaging modality and can visualize biological structures at multiply scales ranging from organelles to organs.However,due to the non-ideal imaging condition like finite detector aperture size,bandwidth or limited view angle,the reconstructed PACT images usually suffer from spatially variant blur,which severely damage the image details.Therefore,we propose a restoration method which is based on deconvolution with spatially variant point spread function(PSF)to improve the quality of the PACT images.Firstly,we design a precise measurement method to obtain the PSFs of certain discrete positions in the PACT system,then we use the principal component analysis(PCA)to transform the obtained spatially variant PSF into a linear combination of some spatially invariant basis PSFs.Therefore,the representation model of spatially variant PSF is constructed.Next,the radial basis interpolation is adopted to achieve the entire spatially variant PSF of the PACT system.Secondly,we describe the problem of image restoration under the framework of Bayesian maximum a posteriori probability.Based on the assumption that the measurement error of the PACT system follows Poisson distribution,we derive the Richardson-Lucy(RL)algorithm with spatially variant PSF.In order to suppress the noise during the image restoration,a new regularization method named sparse logarithmic gradient(SLG)regularization is proposed.We integrate SLG with the RL algorithm(SLG-RL)to improve the stability of restoration.Thirdly,we design a method to remove the streak artifacts in the PACT images obtained with a ring-shape transducer array.Considering the imaging characteristics of ring-shape transducer array,the streak artifacts oscillate approximately periodically,so this method firstly adopts the rotation and average operations to suppress the streak artifacts,then the SLG-RL is adopted once more to remove the blur resulting from rotation and average operations.Finally,we carry out simulation,phantom and in vivo experiments.All the results show that our restoration method can improve the image resolution and remove the streak artifacts effectively.In addition,we also compare the restoration results with different regularizations.The results show that the SLG regularization outperforms classic Tikhonov regularization.In conclusion,the method we proposed is of great significance to better play the role of PACT imaging technology in medical diagnosis.