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Image enhancement of photoacoustic imaging for early endometrial cancer detection by employing a filtered delay multiply and sum beamforming algorithm.

Authors :
Lin, Yongping
Zheng, Rongsheng
Zhang, Xiaoman
Li, Zhifang
Li, Hui
Source :
AIP Advances. Dec2019, Vol. 9 Issue 12, p1-6. 6p.
Publication Year :
2019

Abstract

In endometrial cancer, patients in early stages have a 91% 5-year survival chance. By contrast, patients in advanced stages have only 20% survival chance. Therefore, early diagnosis of endometrial cancer is very important. Photoacoustic imaging is able to distinguish benign from malignant tumors. However, the images acquired through photoacoustic imaging contain inherent artifacts, caused by imperfect reconstruction algorithms. In this paper, to improve the said images, a filtered delay-multiply-and-sum (F-DMAS) algorithm, which was proven to have an increased dynamic range and better quality of B-mode images was employed in the reconstruction process. First, the images of two blood vessel phantom experiments, acquired through photoacoustic imaging, were reconstructed by employing the F-DMAS algorithm. The results show the lateral resolutions of the system improving from 2.22 mm (with traditional photoacoustic imaging reconstruction algorithms) to 1.47 mm. Next, images of a pig uterus, filled with intralipid-20% emulsion, were also reconstructed by employing the F-DMAS algorithm. The average signal-to-noise ratio increased from 11.14 dB (with traditional photoacoustic imaging reconstruction algorithms) to 64.90 dB. In order to improve the continuity of the 3D PA image, F-DMAS with an adaptive coefficient was discussed to find the best balance between the signal-to-noise ratio and continuity. In conclusion, this paper demonstrates that the use of F-DMAS algorithms in the reconstruction of the images acquired through photoacoustic imaging in clinical investigations would improve the detection rate of early endometrial cancer. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21583226
Volume :
9
Issue :
12
Database :
Academic Search Index
Journal :
AIP Advances
Publication Type :
Academic Journal
Accession number :
140975428
Full Text :
https://doi.org/10.1063/1.5122891