Photoacoustic classification of tumor malignancy based on support vector machine

doi:10.1117/12.2500750

	Photoacoustic classification of tumor malignancy based on support vector machine
	Lan, Hengrong1 ; Duan, Tinyang1 ; Zhong, Hongtao1 ; Zhou, Meng1,2 ; Gao, Fei1
	2018
会议录名称	OPTICS IN HEALTH CARE AND BIOMEDICAL OPTICS VIII
卷号	10820
发表状态	已发表
DOI	10.1117/12.2500750
摘要	Accurate diagnosis of malignancy tumor in early stage is great significance to achieve high curability, which could improve survival rate in this stage. Precise classification to differentiate malignancy of tumors is favourable to reduce cost in treatment when there is no obvious features in radiology diagnose in early phase. Photoacoustic tomography (PAT) is a burgeoning new imaging modality, which combines optical contrast and ultrasound penetrating in deep medium. However, it has not been fully exploited on the capability of PAT to discriminate tumor's malignancy. In this paper, a multistatic classification approach in PAT is proposed, which could discriminate malignant/benign tumors based on its morphological feature in clinical diagnosis that tumors usually show different shape irregularity compared with healthy tissue. The multistatic photoacoustic waves were used to extract two different features to differentiate the two types of tumors with high accuracy (>90%) in three different scenarios using Support Vector Machines (SVM). In addition, two conventional PAT image reconstructing algorithms are also performed to reconstruct images as a comparative study, which unfortunately cannot differentiate their malignancy precisely because of limited detector bandwidth and severe acoustic distortion. We performed the feasibility study in this paper with both simulation and experimental results, which shows that the proposed multistatic photoacoustic classification method to distinguish between malignant and benign tumors works well, and could be easily applied for state-of-art array-based PAT system to ameliorate the diagnostic accuracy.
关键词	Photoacoustic imaging support vector machine tumor malignance
出版地	1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA
会议地点	Beijing, China
收录类别	CPCI ; CPCI-S ; EI
语种	英语
资助项目	Natural Science Foundation of China[61805139]
WOS研究方向	Optics
WOS类目	Optics
WOS记录号	WOS:000451757000032
出版者	SPIE-INT SOC OPTICAL ENGINEERING
EI入藏号	20184806158459
EI主题词	Computer aided diagnosis ; Health care ; Image reconstruction ; Photoacoustic effect ; Tumors
EI分类号	Bioengineering and Biology:461 ; Computer Software, Data Handling and Applications:723 ; Computer Applications:723.5 ; Light/Optics:741.1
WOS关键词	SHAPE
原始文献类型	Proceedings Paper
引用统计	正在获取...
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/29030
专题	信息科学与技术学院_博士生信息科学与技术学院_PI研究组_高飞组信息科学与技术学院_硕士生
通讯作者	Gao, Fei
作者单位	1.ShanghaiTech Univ, Sch Informat Sci & Technol, Hybrid Imaging Syst Lab, Shanghai 201210, Peoples R China 2.Chinese Acad Sci, Shanghai Adv Res Inst, Shanghai 201210, Peoples R China
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Lan, Hengrong,Duan, Tinyang,Zhong, Hongtao,et al. Photoacoustic classification of tumor malignancy based on support vector machine[C]. 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA:SPIE-INT SOC OPTICAL ENGINEERING,2018.