Research On Photoacoustic Image Reconstruction And Its Application

The application of compressed sensing for photoacoustic image reconstruction has been developed for different purpose. The photoacoustic image actually associating to the optical absorption distribution of the target, which reconstructed by the sampling acoustic signals generated from biological tissues that absorbed electromagnetic energy delivered by non-ionizing laser pulses. As a non-invasive medical imaging technique, photoacoustic imaging brings higher resolution and more sensitive to endogenous optical contrast than optical imaging and acoustic imaging, which have great potential in the early diagnosis of lesions.Compressed sensing attracted a lot of interest after it’s been proposed. It takes advantage of the redundancy in many interesting signals—they are not pure noise. By knowing the signal’s sparseness or compressibility in some domain in advance, allowing the entire signal to be determined from relatively few measurements. Many algorithms with compressed sensing have been developed in signal processing, digital image processing.In this paper, we propose a photoacoustic image reconstruction method with compressed sensing. How to reduce the number of needed transducers is an important task, and it can be accomplished by combining compressed sensing in photoacoustic imaging. Sound velocity correction in tissue is a tough issue, the accuracy of sound speed is important to photoacoustic image reconstruction. In order to deal with this, we propose a sound velocity correction method by reconstructing the photoacoustic image iteratively, and then pick up the most correct sound speed. The main contents in this paper include:1) Photoacoustic spectroscopy and photoacoustic imaging. Introduce the mathematical model of photoacoustic spectroscopy and the commonly used photoacoustic imaging method. Accomplish the delay and sum method, which is used in sound velocity correction method.2) Compressed sensing. Introduce the compressed sensing theory and its applications. Accomplish the orthogonal matching pursuit algorithm for signal reconstruction, which is used in our photoacoustic image reconstruction method.3) Photoacoustic image reconstruction with compressed sensing. Introduce a photoacoustic image reconstruction method with compressed sensing, deduce and accomplish its detailed steps.4) Sound velocity correction based on photoacoustic imaging. Introduce the sound velocity correction method with delay and sum photoacoustic image reconstruction algorithm, deduce and accomplish its detailed steps.Photoacoustic imaging has great potential in the future because of it born with the advantages both of acoustic imaging and optical imaging. The photoacoustic image reconstruction method proposed in this paper reduce the number of needed transducers by applying compressed sensing theory, and the sound velocity correction method focus on how to solve the problem of sound velocity measurement in complex tissue. Furthermore, there are some parts, like filter the noise, reduce the memory cost in reconstruction and accelerate the compute in sound velocity correction, need to be further study.