目的 对数字减影血管造影(digital subtraction angiography,DSA)图像进行处理,获取肝脏肿瘤的供血血管图像,为肿瘤介入栓塞治疗提供依据,并对栓塞效果进行评价。方法 在MATLAB平台上,分别对治疗前、治疗后及肿瘤图像进行处理,获得肝脏肿瘤供血的血管图像和治疗后的肝脏血管图像。结果 实现了肝脏肿瘤、肝脏肿瘤供血血管和肝脏血管图像的提取。结论 对于随机抽取的DSA图像,该方法可获得理想的肝脏血管图像和为肝脏肿瘤供血的血管图像,可为临床医生的治疗提供依据,还可为科研及教学服务,具有一定的实用价值。
Abstract
Objective: To obtain the blood supply vessels of the liver tumor through processing the digital subtraction angiography (DSA) image, and to provide the clinical treatment basis for the detection of tumor interventional therapy and embolization. Methods: The tumor images, the blood vessels and liver vessels were obtained before and after being processed on the MATLAB platform . Results: The extraction of liver tumor, blood supply vessel of liver tumor and blood vessel of liver were realized. Conclusion: For randomly selected DSA images, this method can obtain ideal liver blood vessels and blood vessels for liver tumors, which can provide basis for the treatment of clinicians, and serve for scientific research and teaching.
关键词
DSA/图像处理/肿瘤供血血管/肝脏血管
Key words
DSA/image processing/tumor blood supply vessel/hepatic vessels
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 李梦霞,李启勇,肖憨,等.原发性肝脏神经内分泌肿瘤的诊断和治疗进展[J].临床医学进展, 2019,9(3):225-234.
[2] 傅毅振,陈敏山. 2019年原发性肝癌治疗进展[J].肿瘤综合治疗电子杂志, 2020,6(2):86-89.
[3] Malarvezhi P, Kumar R. A diversity enhanced particle filter for carrier frequency offset estimation in nonlinear OFDM system[J]. Wireless Pers Commun, 2016, 89(1): 15-26.
[4] Dawood H, Guo P. Generalization of impulse noise removal[J].Int Arab J Inf Techn, 2017, 14(5): 698-706.
[5] Xu P, Roosta F, Mahoney MW. Newton-type methods for non-convex optimization under inexact Hessian information[J]. Math Program, 2017, 25(6): 1-36.
[6] Arguello F, Vilarino DL, Heras DB, et al. GPU-based segmentation of retinal blood vessels [J]. J Real-Time Image PR, 2018, 14(4): 773-782.
[7] Ronot M, Abdelrehim M, Hakime A, et al. Cone-Beam CT angiography for determination of tumor-feeding vessels during chemoembolization of liver tumors: comparison of conventional and dedicated-software analysis[J]. Journal of Vascular and Interventional Radiology,2016,27(1):32-38.
[8] Tim J, Franjo P, Bostjan N, et al. Enhancement of vascular structures in 3D and 2D angiographic images[J]. IEEE Transactions on Medical Imaging,2016,35(9):2017-2118.
[9] Opolski MP, Pregowski J, Kruk M, et al. Quantitative evaluation of noise reduction and vesselness filters for liver vessel segmentation on abdominal CTA images[J]. Physics in medicine and biology,2015,60(10):3905-3926.
[10] Levi Sandri GB, Lai Q, Lucatelli P. The forgotten place of radioembolization for the treatment of hepatocellular carcinoma with portal vein tumour thrombosis[J]. Liver Int, 2017,37(6):469-470.
[11] Miyayama S, Yamashiro M, Nagai K, et al. Efficacy of automated tumor-feeder detection software using cone-beam computed tomography technology in transarterial embolization through extrahepatic collateral vessels for malignant hepatic tumors[J]. Hepatol Res, 2016,46(11):166-173.
[12] Lucatelli P, Argiro R, GinanniCorradini S, et al. Comparison of image quality and diagnostic performance of Cone-Beam CT during drug-eluting embolic transarterial chemoembolization and multidetector CT in the detection of hepatocellular carcinoma[J]. J VascInterv Radiol, 2017,28(6):978-986.
[13] Schernthaner RE, Chapiro J, Sahu S, et al. Feasibility of a modified Cone-Beam CT rotation trajectory to improve liver periphery visualization during transarterial chemoembolization[J]. Radiology, 2015,7(277):833-841.
[14] Kinoshita M, Takechi K, Iwamoto S, et al. The usefulness of cone-beam computed tomography during chemoembolization of hepatocellular carcinomas fed exclusively by the cystic artery[J]. Japanese Journal of Radiology,2016,34(4):747-753.
[15] Wang Z, Chen R, Duran R, et al. Intraprocedural 3D quantification of lipiodol deposition on Cone-Beam CT predicts tumor response after transarterial chemoembolization in patients with hepatocellular carcinoma[J]. Cardiovasc InterventRadiol, 2015,38(8):1548-1556.
[16] Yoneyama S, Koyanagi J, Arikawa S. Measurement of discontinuous displacement/strain using mesh-based digital image correlation[J]. Advanced Composite Materials, 2015, 25(4):329-343.
基金
国家自然科学基金(81371531);泰安市科技计划(2019NS143)。