基本信息
王坤  男  硕导  中国科学院自动化研究所
电子邮件: kun.wang@ia.ac.cn
通信地址: 北京市海淀区中关村东路95号,中国科学院自动化研究所,智能大厦903
邮政编码: 100190

研究领域

专注于分子影像、医学影像人工智能等前沿领域的技术研发和临床应用。研究工作覆盖了相关医学成像技术的模型算法研究,仪器设备研发,生物医学应用与临床医学转化。其研究目标是利用光学多模融合分子影像技术和影像组学大数据人工智能分析技术,提高肿瘤等重大疾病的影像检测灵敏度和定量分析精确度,从而促进疾病的早期检测和精准治疗的发展。以第一或通讯作者(含并列)在GutAdvanced Materials、Engineering、Nature Communications、Medical Image Analysis、Optica、IEEE Transactions on Medical ImagingSCI检索期刊发表论文50余篇,另获得授权国家发明专利十余项。先后承担国家自然科学基金委青年项目、面上项目、重大研究计划集成项目子课题,中国科学院科技服务网络计划(STS计划)重点项目、科研仪器设备研发项目;荣获中国科学院青年创新促进会优秀会员;并作为课题骨干参与国家重大科研仪器设备研制专项、国家重点基础研究发展计划(973计划)、国家重点研发计划纳米科技重点专项等。 现任IEEE医学和生物工程学会北京分会秘书长,中国医师协会放射医师分会第四届专业委员会委员,中国研究型医院学会消化内镜分子影像学专业委员会常务委员,以及中国科学院青年创新促进会会员。曾担任世界分子影像大会(World Molecular Imaging Congress2015年执行委员会委员,以及中国生物物理学会分子影像专业委员会副秘书长(2014-2017年)。

招生信息

   
招生专业
081203-计算机应用技术
招生方向
医学影像与人工智能
医学影像设备与装备
多模态分子影像

教育背景

2008-01--2011-12   英国纽卡斯尔大学医学院   医学影像博士
2006-09--2007-12   比利时鲁汶大学医学院   医学影像硕士
2005-09--2006-07   比利时鲁汶大学工程学院   电子电气工程硕士
2003-09--2005-07   比利时鲁汶大学工程学院   电子电气工程学士
2002-09--2006-07   北京交通大学电子信息技术学院   通讯工程学士

工作经历

   
工作简历
2021-01~现在, 中国科学院自动化研究所, 研究员
2014-10~2021-01,中国科学院自动化研究所, 副研究员
2012-11~2014-10,中国科学院自动化研究所, 助理研究员
学术兼职
2020-01-01-今,中国抗癌协会肿瘤人工智能专业委员会委员,
2020-01-01-今,中国研究型医院学会超声医学专业委员会委员,
2018-01-01-今,中国医师协会放射医师分会第四届专业委员会委员,
2016-01-01-今,中国科学院青年创新促进会会员,
2014-12-31-2015-12-30,世界分子影像学会程序委员会委员,
2014-01-01-今,IEEE医学和生物工程学会北京分会秘书,
2013-12-30-2017-12-31,中国生物物理学会分子影像专业委员会副秘书长,

专利与奖励

   
专利成果
[1] 田捷, 孟慧, 王坤, 高源. 基于K近邻局部连接网络的光学断层成像方法、系统. CN: CN110974166B, 2021-03-12.

[2] 田捷, 张鹏, 惠辉, 王坤, 杨鑫. 基于FFL的磁粒子成像三维立体重建方法、系统、装置. CN: CN110420026A, 2019-11-08.

[3] 田捷, 惠辉, 张鹏, 王坤, 杨鑫. 基于无磁场线扫描的磁粒子成像系统. CN: CN110367983A, 2019-10-25.

[4] 田捷, 孟慧, 王坤, 高源. 基于非局部全变分规则化的激发荧光断层成像方法. CN: CN109658463A, 2019-04-19.

[5] 田捷, 孟慧, 王坤, 高源. 基于自适应高斯拉普拉斯规则化的FMT重建方法及装置. CN: CN109615673A, 2019-04-12.

[6] 田捷, 孟慧, 王坤, 高源. 基于深度学习的显微荧光图像分类方法. CN: CN109447185A, 2019-03-08.

[7] 田捷, 王坤, 黄超, 安羽. 基于深度学习的激发荧光断层成像三维重建方法. CN: CN109191564A, 2019-01-11.

[8] 田捷, 王坤, 安羽, 高源. 基于多层感知网络的激发荧光断层成像方法. CN: CN109166103A, 2019-01-08.

[9] 田捷, 王坤, 高源, 安羽, 周辉. 基于多层感知机的生物自发荧光三维成像方法. CN: CN108451508A, 2018-08-28.

[10] 田捷, 王坤, 高源, 尹琳. 实验动物体多模融合成像系统及使用方法. CN: CN108335338A, 2018-07-27.

[11] 田捷, 靳玉慎, 王坤. 肝细胞癌诊断试剂及其制备方法. CN: CN108245688A, 2018-07-06.

[12] 田捷, 王坤, 李辉, 彭冬, 朱玉坤. 一种光声成像和光学成像多模态融合成像系统. CN: CN106124469A, 2016-11-16.

[13] 田捷, 王坤, 高源, 张爽, 刘红波. 基于纯光学系统的生物自发光三维成像方法. CN: CN106097437A, 2016-11-09.

[14] 田捷, 朱玉坤, 王坤, 邱晨, 李辉. 一种用于光动力治疗的靶向探针及制备方法. CN: CN105879029A, 2016-08-24.

[15] 胡振华, 田捷, 宋天明, 王坤. 基于契伦科夫效应的内窥平面成像系统和方法. CN: CN104027064A, 2014-09-10.

[16] 田捷, 刘振宇, 董迪, 杨鑫, 王坤, 彭冬. 一种光声与X射线断层成像融合的成像系统. CN: CN103690244A, 2014-04-02.

[17] 田捷, 吴萍, 杨鑫, 王坤. 一种基于迭代重加权的生物自发荧光断层成像方法. CN: CN103300829A, 2013-09-18.

出版信息

   
部分发表论文
[1] Tong, Tong, Li, Dongyang, Gu, Jionghui, Chen, Guo, Bai, Guotao, Yang, Xin, Wang, Kun, Jiang, Tianan, Tian, Jie. Dual-Input Transformer: An End-to-End Model for Preoperative Assessment of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Ultrasonography. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS[J]. 2023, 27(1): 251-262, http://dx.doi.org/10.1109/JBHI.2022.3216031.
[2] Huang, Weiyuan, Wang, Kun, Chen, Fengxia, Li, Gao, Chen, Xianshan, Yang, Qianyu, Li, Na, He, Kunshan, Chen, Feng, Tian, Jie. Intraoperative Fluorescence Visualization in Thoracoscopic Surgery. ANNALS OF THORACIC SURGERY[J]. 2023, 115(3): e79-e81, http://dx.doi.org/10.1016/j.athoracsur.2022.03.040.
[3] Kun Wang, Yang Du, Zeyu Zhang, Kunshan He, Zhongquan Cheng, Lin Yin, Di Dong, Changjian Li, Wei Li, Zhenhua Hu, Chong Zhang, Hui Hui, Chongwei Chi, Jie Tian. Fluorescence image-guided tumour surgery. Nature Reviews Bioengineering[J]. 2023, 1(3): 161-179, [4] Zheling Meng, Yangyang Zhu, Wenjing Pang, Jie Tian, Fang Nie, Kun Wang. MSMFN: An ultrasound based multi-step modality fusion network for identifying the histologic subtypes of metastatic cervical lymphadenopathy. IEEE TRANSACTIONS ON MEDICAL IMAGING[J]. 2023, 42(4): 996-1008, [5] An, Chao, Li, Dongyang, Li, Sheng, Li, Wangzhong, Tong, Tong, Liu, Lizhi, Jiang, Dongping, Jiang, Linling, Ruan, Guangying, Hai, Ning, Fu, Yan, Wang, Kun, Zhuo, Shuiqing, Tian, Jie. Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING[J]. 2022, 49(4): 1187-1199, http://dx.doi.org/10.1007/s00259-021-05573-z.
[6] Tong, Tong, Gu, Jionghui, Xu, Dong, Song, Ling, Zhao, Qiyu, Cheng, Fang, Yuan, Zhiqiang, Tian, Shuyuan, Yang, Xin, Tian, Jie, Wang, Kun, Jiang, Tianan. Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis. BMC MEDICINE[J]. 2022, 20(1): https://doaj.org/article/26ec078e68ed417abaa7872dc7e9517c.
[7] Huang, Wenhui, Wang, Kun, Huang, Weiyuan, He, Zicong, Zhang, Jingming, Zhang, Bin, Xiong, Zhiyuan, Gillen, Kelly McCabe, Li, Wenzhe, Chen, Feng, Yang, Xing, Zhang, Shuixing, Tian, Jie. Carbonic anhydrase IX stratifies patient prognosis and identifies nodal status in animal models of nasopharyngeal carcinoma using a targeted imaging strategy. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING[J]. 2022, 49(13): 4427-4439, http://apps.webofknowledge.com/CitedFullRecord.do?product=UA&colName=WOS&SID=5CCFccWmJJRAuMzNPjj&search_mode=CitedFullRecord&isickref=WOS:000836079200002.
[8] Zhu, Yangyang, Meng, Zheling, Fan, Xiao, Duan, Yin, Jia, Yingying, Dong, Tiantian, Wang, Yanfang, Song, Juan, Tian, Jie, Wang, Kun, Nie, Fang. Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy. BMC MEDICINE[J]. 2022, 20(1): http://dx.doi.org/10.1186/s12916-022-02469-z.
[9] Zhang, Chong, Wang, Kun, Tian, Jie. Adaptive brightness fusion method for intraoperative near-infrared fluorescence and visible images. BIOMEDICAL OPTICS EXPRESS[J]. 2022, 13(3): 1243-1260, http://dx.doi.org/10.1364/BOE.446176Journal.
[10] Gu, Jionghui, Tong, Tong, He, Chang, Xu, Min, Yang, Xin, Tian, Jie, Jiang, Tianan, Wang, Kun. Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study. EUROPEAN RADIOLOGY[J]. 2022, 32(3): 2099-2109, http://dx.doi.org/10.1007/s00330-021-08293-y.
[11] Huang, Qi, Wang, Kun, Wanggou, Siyi, Tian, Jie, Li, Xuejun. A novel co-targeting strategy of EGFR/SEC61G for multi-modality fluorescence/MR/photoacoustic imaging of glioblastoma. NANOMEDICINE-NANOTECHNOLOGY BIOLOGY AND MEDICINE[J]. 2022, 40: http://dx.doi.org/10.1016/j.nano.2021.102509.
[12] Ma, QiuPing, He, Xuelei, Li, Kai, Wang, Jinfen, Zeng, QingJing, Xu, ErJiao, He, Xuqi, Li, Shuoyang, Kun, Wang, Zheng, RongQin, Tian, Jei. Dynamic Contrast-Enhanced Ultrasound Radiomics for Hepatocellular Carcinoma Recurrence Prediction After Thermal Ablation. MOLECULAR IMAGING AND BIOLOGY[J]. 2021, 23(4): 572-585, http://dx.doi.org/10.1007/s11307-021-01578-0.
[13] Huang, Wenhui, Wu, Qingxia, Chen, Zhuozhi, Xiong, Zhiyuan, Wang, Kun, Tian, Jie, Zhang, Shuixing. The potential indicators for pulmonary fibrosis in survivors of severe COVID-19. JOURNAL OF INFECTION. 2021, 82(2): E5-E7, http://dx.doi.org/10.1016/j.jinf.2020.09.027.
[14] Lu, Xue, Zhou, Hui, Wang, Kun, Jin, Jieyang, Meng, Fankun, Mu, Xiaojie, Li, Shuoyang, Zheng, Rongqin, Tian, Jie. Comparing radiomics models with different inputs for accurate diagnosis of significant fibrosis in chronic liver disease. EUROPEAN RADIOLOGY[J]. 2021, 31(11): 8743-8754, http://dx.doi.org/10.1007/s00330-021-07934-6.
[15] Qian, Lang, Lv, Zhikun, Zhang, Kai, Wang, Kun, Zhu, Qian, Zhou, Shichong, Chang, Cai, Tian, Jie. Application of deep learning to predict underestimation in ductal carcinoma in situ of the breast with ultrasound. ANNALS OF TRANSLATIONAL MEDICINE[J]. 2021, 9(4): http://dx.doi.org/10.21037/atm-20-3981.
[16] Yin, Lin, Wang, Kun, Tong, Tong, Wang, Qian, An, Yu, Yang, Xin, Tian, Jie. Adaptive Grouping Block Sparse Bayesian Learning Method for Accurate and Robust Reconstruction in Bioluminescence Tomography. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING[J]. 2021, 68(11): 3388-3398, http://dx.doi.org/10.1109/TBME.2021.3071823.
[17] Dong, Di, Tang, Zhenchao, Wang, Shuo, Hui, Hui, Gong, Lixin, Lu, Yao, Xue, Zhong, Liao, Hongen, Chen, Fang, Yang, Fan, Jin, Ronghua, Wang, Kun, Liu, Zhenyu, Wei, Jingwei, Mu, Wei, Zhang, Hui, Jiang, Jingying, Tian, Jie, Li, Hongjun. The Role of Imaging in the Detection and Management of COVID-19: A Review. IEEE REVIEWS IN BIOMEDICAL ENGINEERINGnull. 2021, 14: 16-29, http://apps.webofknowledge.com/CitedFullRecord.do?product=UA&colName=WOS&SID=5CCFccWmJJRAuMzNPjj&search_mode=CitedFullRecord&isickref=WOS:000708445300006.
[18] Yin, Lin, Cao, Zhen, Wang, Kun, Tian, Jie, Yang, Xing, Zhang, Jianhua. A review of the application of machine learning in molecular imaging. ANNALS OF TRANSLATIONAL MEDICINE[J]. 2021, 9(9): http://dx.doi.org/10.21037/atm-20-5877.
[19] Liu, Fei, Wang, Kun, Liu, Dan, Yang, Xin, Tian, Jie. Deep pyramid local attention neural network for cardiac structure segmentation in two-dimensional echocardiography. MEDICAL IMAGE ANALYSIS[J]. 2021, 67: http://dx.doi.org/10.1016/j.media.2020.101873.
[20] Tong, Tong, Huang, Wenhui, Wang, Kun, He, Zicong, Yin, Lin, Yang, Xin, Zhang, Shuixing, Tian, Jie. Domain Transform Network for Photoacoustic Tomography from Limited-view and Sparsely Sampled Data. PHOTOACOUSTICS[J]. 2020, 19: https://doaj.org/article/c9472c0de9ec43ada91badfc84cc4bd7.
[21] Liu, Dan, Liu, Fei, Xie, Xiaoyan, Su, Liya, Liu, Ming, Xie, Xiaohua, Kuang, Ming, Huang, Guangliang, Wang, Yuqi, Zhou, Hui, Wang, Kun, Lin, Manxia, Tian, Jie. Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound. EUROPEAN RADIOLOGY[J]. 2020, 30(4): 2365-2376, http://dx.doi.org/10.1007/s00330-019-06553-6.
[22] He, Kunshan, Hong, Xiaopeng, Chi, Chongwei, Cai, Chaonong, Wang, Kun, Li, Peiping, Liu, Xialei, Li, Jian, Shan, Hong, Tian, Jie. A new method of near-infrared fluorescence image-guided hepatectomy for patients with hepatolithiasis: a randomized controlled trial. SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES[J]. 2020, 34(11): 4975-4982, https://www.webofscience.com/wos/woscc/full-record/WOS:000511080200001.
[23] Yin, Tinghui, Wang, Kun, Qiu, Chen, Zhang, Xinling, Zhou, Huichao, You, Yujia, Ren, Jie, Mao, Ren, Yang, Biying, Miao, Xiaoyan, Tian, Jie, Zheng, Rongqin. Simple structural indocyanine green-loaded microbubbles for dual-modality imaging and multi-synergistic photothermal therapy in prostate cancer. NANOMEDICINE-NANOTECHNOLOGY BIOLOGY AND MEDICINE[J]. 2020, 28: http://dx.doi.org/10.1016/j.nano.2020.102229.
[24] Meng, Hui, Gao, Yuan, Yang, Xin, Wang, Kun, Tian, Jie. K-Nearest Neighbor Based Locally Connected Network for Fast Morphological Reconstruction in Fluorescence Molecular Tomography. IEEETRANSACTIONSONMEDICALIMAGING[J]. 2020, 39(10): 3019-3028, http://dx.doi.org/10.1109/TMI.2020.2984557.
[25] Jiang, Shixin, Liu, Jie, An, Yu, Gao, Yuan, Meng, Hui, Wang, Kun, Tian, Jie. Fluorescence Molecular Tomography Based on Group Sparsity Priori for Morphological Reconstruction of Glioma. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING[J]. 2020, 67(5): 1429-1437, https://www.webofscience.com/wos/woscc/full-record/WOS:000530299200021.
[26] An Yu, Meng Hui, Gao Yuan, Tong Tong, Zhang Chong, Wang Kun, Tian Jie. Application of machine learning method in optical molecular imaging: a review. SCIENCE CHINA. INFORMATION SCIENCE[J]. 2020, 63(1): 16-, http://sciencechina.cn/gw.jsp?action=detail.jsp&internal_id=6655412&detailType=1.
[27] Zhou, Hui, Wang, Kun, Tian, Jie. Online Transfer Learning for Differential Diagnosis of Benign and Malignant Thyroid Nodules With Ultrasound Images. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING[J]. 2020, 67(10): 2773-2780, http://dx.doi.org/10.1109/TBME.2020.2971065.
[28] Liang, Xin, Wang, Kun, Du, Jiangfeng, Tian, Jie, Zhang, Hui. The first visualization of chemotherapy-induced tumor apoptosis via magnetic particle imaging in a mouse model. PHYSICS IN MEDICINE AND BIOLOGY[J]. 2020, 65(19): http://dx.doi.org/10.1088/1361-6560/abad7c.
[29] 王坤. In vivo three-dimensional evaluation of tumor hypoxia in nasopharyngeal carcinomas using FMT-CT and MSOT. European Journal of Nuclear Medicine and Molecular Imaging. 2020, [30] Yin, Lin, Wang, Kun, Tong, Tong, An, Yu, Meng, Hui, Yang, Xin, Tian, Jie. Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING[J]. 2020, 67(7): 2023-2032, http://dx.doi.org/10.1109/TBME.2019.2953732.
[31] Liu, Fei, Liu, Dan, Wang, Kun, Xie, Xiaohua, Su, Liya, Kuang, Ming, Huang, Guangliang, Peng, Baogang, Wang, Yuqi, Lin, Manxia, Tian, Jie, Xie, Xiaoyan. Deep Learning Radiomics Based on Contrast-Enhanced Ultrasound Might Optimize Curative Treatments for Very-Early or Early-Stage Hepatocellular Carcinoma Patients. LIVER CANCER[J]. 2020, 9(4): 397-413, https://doaj.org/article/6c95af51c58d47ef937f6d94f8f7ae76.
[32] Huang, Wenhui, Wang, Kun, An, Yu, Meng, Hui, Gao, Yuan, Xiong, Zhiyuan, Yan, Hao, Wang, Qian, Cai, Xuekang, Yang, Xin, Zhang, Bin, Chen, Qiuying, Yang, Xing, Tian, Jie, Zhang, Shuixing. In vivo three-dimensional evaluation of tumour hypoxia in nasopharyngeal carcinomas using FMT-CT and MSOT. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING[J]. 2020, 47(5): 1027-1038, http://dx.doi.org/10.1007/s00259-019-04526-x.
[33] Liu, Fei, Liu, Dan, Tian, Jie, Xie, Xiaoyan, Yang, Xin, Wang, Kun. Cascaded one-shot deformable convolutional neural networks: Developing a deep learning model for respiratory motion estimation in ultrasound sequences. MEDICAL IMAGE ANALYSIS[J]. 2020, 65: http://dx.doi.org/10.1016/j.media.2020.101793.
[34] Zhang, Peng, Liu, Jie, Hui, Hui, An, Yu, Wang, Kun, Yang, Xin, Tian, Jie. Linear scheme for the direct reconstruction of noncontact time-domain fluorescence molecular lifetime tomography. APPLIED OPTICS[J]. 2020, 59(26): 7961-7967, https://www.webofscience.com/wos/woscc/full-record/WOS:000571484700029.
[35] Zhou, Hui, Jin, Yinhua, Dai, Lei, Zhang, Meiwu, Qiu, Yuqin, Wang, Kun, Tian, Jie, Zheng, Jianjun. Differential Diagnosis of Benign and Malignant Thyroid Nodules Using Deep Learning Radiomics of Thyroid Ultrasound Images. EUROPEAN JOURNAL OF RADIOLOGY[J]. 2020, 127(127): http://dx.doi.org/10.1016/j.ejrad.2020.108992.
[36] Wang, Qian, Yan, Hao, Wang, Zihua, Li, Zhangfu, Li, Dan, Li, Zheng, Wang, Kun, Tian, Jie, Zhao, Xinming. Construction of a novel bispecific fusion protein to enhance targeting for pancreatic cancer imaging. BIOMATERIALS[J]. 2020, 255(255): http://dx.doi.org/10.1016/j.biomaterials.2020.120161.
[37] Jiang, Shixin, Liu, Jie, Zhang, Guanglei, An, Yu, Meng, Hui, Gao, Yuan, Wang, Kun, Tian, Jie. Reconstruction of Fluorescence Molecular Tomography via a Fused LASSO Method Based on Group Sparsity Prior. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING[J]. 2019, 66(5): 1361-1371, http://ir.ia.ac.cn/handle/173211/24233.
[38] Gao, Lei, Hu, Yong, Tian, Yahui, Fan, Zhenzhen, Wang, Kun, Li, Hongdan, Zhou, Qian, Zeng, Guandi, Hu, Xin, Yu, Lei, Zhou, Shiyu, Tong, Xinyuan, Huang, Hsinyi, Chen, Haiquan, Liu, Qingsong, Liu, Wanting, Zhang, Gong, Zeng, Musheng, Zhou, Guangbiao, He, Qingyu, Ji, Hongbin, Chen, Liang. Lung cancer deficient in the tumor suppressor GATA4 is sensitive to TGFBR1 inhibition. NATURE COMMUNICATIONS[J]. 2019, 10(1): https://doaj.org/article/a22e2b802e16470085f09c63c8826bf0.
[39] Meng, Hui, Wang, Kun, Gao, Yuan, Jin, Yushen, Ma, Xibo, Tian, Jie. Adaptive Gaussian Weighted Laplace Prior Regularization Enables Accurate Morphological Reconstruction in Fluorescence Molecular Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING[J]. 2019, 38(12): 2726-2734, http://dx.doi.org/10.1109/TMI.2019.2912222.
[40] Zhou, Qunfang, Wang, Kun, Dou, Jianping, Cao, Feng, Liu, Fengyong, Yuan, Hongjun, Mu, Mengjuan, Xu, Jinshun, Zhang, Dongyun, Li, Xin, Tian, Jie, Yu, Jie, Liang, Ping. Theranostic liposomes as nanodelivered chemotherapeutics enhanced the microwave ablation of hepatocellular carcinoma. NANOMEDICINE[J]. 2019, 14(16): 2151-2167, [41] Zhang, Chong, Wang, Kun, An, Yu, He, Kunshan, Tong, Tong, Tian, Jie. Improved generative adversarial networks using the total gradient loss for the resolution enhancement of fluorescence images. BIOMEDICAL OPTICS EXPRESS[J]. 2019, 10(9): 4742-4756, http://dx.doi.org/10.1364/BOE.10.004742.
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[60] Shang, Wenting, Zeng, Chaoting, Du, Yang, Hui, Hui, Liang, Xiao, Chi, Chongwei, Wang, Kun, Wang, Zhongliang, Tian, Jie. Core-Shell Gold Nanorod@Metal-Organic Framework Nanoprobes for Multimodality Diagnosis of Glioma. ADVANCEDMATERIALS[J]. 2017, 29(3): https://www.webofscience.com/wos/woscc/full-record/WOS:000392729800020.
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[62] Mao, Yamin, Wang, Kun, He, Kunshan, Ye, Jinzuo, Yang, Fan, Zhou, Jian, Li, Hao, Chen, Xiuyuan, Wang, Jun, Chi, Chongwei, Tian, Jie. Development and application of the near-infrared and white-light thoracoscope system for minimally invasive lung cancer surgery. JOURNAL OF BIOMEDICAL OPTICS[J]. 2017, 22(6): http://dx.doi.org/10.1117/1.JBO.22.6.066002.
[63] Sun, Mengmeng, Liu, Fei, Zhu, Yukun, Wang, Wansheng, Hu, Jin, Liu, Jing, Dai, Zhifei, Wang, Kun, Wei, Yen, Bai, Jing, Gao, Weiping. Salt-induced aggregation of gold nanoparticles for photoacoustic imaging and photothermal therapy of cancer. NANOSCALE[J]. 2016, 8(8): 4452-4457, https://www.webofscience.com/wos/woscc/full-record/WOS:000371117900004.
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[65] Liang, Xiaoyuan, Shang, Wenting, Chi, Chongwei, Zeng, Chaoting, Wang, Kun, Fang, Chihua, Chen, Qingshan, Liu, Huiyu, Fan, Yingfang, Tian, Jie. Dye-conjugated single-walled carbon nanotubes induce photothermal therapy under the guidance of near-infrared imaging. CANCER LETTERS[J]. 2016, 383(2): 243-249, http://dx.doi.org/10.1016/j.canlet.2016.09.006.
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科研活动

   
科研项目
( 1 ) 基于多光谱混合组织特异性模型的契伦科夫荧光高精度三维成像研究, 负责人, 国家任务, 2015-01--2017-12
( 2 ) 脑胶质瘤精准诊疗技术的关键科学问题研究, 参与, 国家任务, 2015-01--2019-12
( 3 ) 小动物光学和光声断层多模融合分子影像设备, 参与, 中国科学院计划, 2014-01--2015-12
( 4 ) 小动物光学多模融合分子影像成像设备, 参与, 国家任务, 2013-01--2017-12
( 5 ) 外源性与内源性光学三维断层成像融合新方法研究, 负责人, 国家任务, 2017-01--2020-12
( 6 ) 动物活体多通道多功能近红外术中成像设备, 负责人, 中国科学院计划, 2019-01--2020-12
( 7 ) 乳腺癌术中多通道近红外成像系统研发及示范应用, 负责人, 中国科学院计划, 2019-01--2023-06
( 8 ) 基于近红外纳米探针的肝癌分子影像及其手术导航技术研发, 参与, 国家任务, 2017-07--2022-06
( 9 ) 肝癌演进监测与治疗决策的分子功能多模态超声可视化研究, 负责人, 国家任务, 2022-01--2025-12
( 10 ) 中国科学院青年创新促进会优秀会员项目, 负责人, 中国科学院计划, 2021-01--2023-12