甄鑫，博士，教授，博導。2013年畢業於南方醫科大學生物醫學工程專業，美國加州大學聖地亞哥分校Moores 腫瘤中心CART 實驗室訪問學者（2011-2012），美國德州大學西南醫學中心腫瘤放射治療系訪問助理教授（2016-），主要研究方向為醫學圖像處理，自適應放射治療，腫瘤放射物理等。
基本介紹
- 中文名：甄鑫
- 國籍：中國
- 畢業院校：南方醫科大學
學習經歷,工作經歷,研究方向,主要獲獎情況,科研課題,代表性論文,
學習經歷
2010.9-2013.6 南方醫科大學，生物醫學工程，博士
2005.9-2008.6 南方醫科大學，生物醫學工程，碩士
2000.9-2005.6 南方醫科大學，生物醫學工程，學士
工作經歷
2021.1-至今 南方醫科大學生物醫學工程學院醫療儀器研究所，教授，博導
2016.2-2017.8美國德州大學西南醫學中心腫瘤放射治療系訪問助理教授
2014.12-2020.12 南方醫科大學生物醫學工程學院醫療儀器研究所，副教授，碩導
2011.7-2012.8美國加州大學聖地亞哥分校Moores 腫瘤中心CART 實驗室訪問學者
2010.12-2014.12 南方醫科大學生物醫學工程學院醫療儀器研究所，講師
2008.7-2010.12 南方醫科大學生物醫學工程學院醫療儀器研究所，助教
研究方向
腫瘤放射物理，影像輔助診斷，信息融合，醫學圖像處理，機器學習在放療中的套用研究等
主要獲獎情況
2012年，AAPM California Chapter Norm Baily Award 2012, best student paper.
2013年，獲中國人民解放軍醫療成果獎三等獎
2014年，獲美國近距離放射治療2014年會（American Brachytherapy Society 2014 Meeting）Top Four Abstract- Best in Physics
2017年，獲美國美國醫學物理學家協會（American Association of Physicists in Medicine，AAPM）2017年會Science Council Session論文獎
科研課題
1. 2018年，國家自然科學基金-面上項目-基於多模態特徵和多分類器的宮頸癌放療直腸毒性預測模型研究（主持）
2. 2017年，國家自然科學基金海外及港澳學者合作研究基金-基於深度學習的宮頸癌放療併發症預測模型研究（主持）
3.2015 年，廣東省自然科學基金面上項目—套用於宮頸癌自適應近距離放療的精確變形配準模型研究（主持）
4.2014 年，廣州市科技計畫項目-珠江科技新星專項—自適應近距離放療中治療分次間CT 圖像變形配準算法研究（主持）
5.2013 年，國家自然科學基金青年基金項目—自適應放療中CT 和信息缺失CBCT 圖像快速變形配準方法的研究（主持）
代表性論文
1. J Wu, F Liang, R Wei, S Lai, X Lv, S Luo, Z Wu, H Chen, W Zhang, X Zeng, X Ye, Y Wu, X Wei, X Jiang, X Zhen, R Yang: A Multiparametric MR-Based RadioFusionOmics Model with Robust Capabilities of Differentiating Glioblastoma Multiforme from Solitary Brain Metastasis. Cancers 2021, 13(22):5793.
2. S Luo, R Wei, S Lu, S Lai, J Wu, Z Wu, X Pang, X Wei, X Jiang, X Zhen, R Yang: Fuhrman nuclear grade prediction of clear cell renal cell carcinoma: influence of volume of interest delineation strategies on machine learning-based dynamic enhanced CT radiomics analysis. European Radiology 2021.
3. L Wang, Q He, X Wang, T Song, X Li, S Zhang, G Qin, W Chen, L Zhou, X Zhen: Multi-criterion decision making-based multi-channel hierarchical fusion of digital breast tomosynthesis and digital mammography for breast mass discrimination. Knowledge-Based Systems 2021, 228:107303.
4. W Zhang, R Yang, F Liang, G Liu, A Chen, H Wu, S Lai, W Ding, X Wei, X Zhen, X Jiang: Prediction of Microvascular Invasion in Hepatocellular Carcinoma With a Multi-Disciplinary Team-Like Radiomics Fusion Model on Dynamic Contrast-Enhanced Computed Tomography. Frontiers in Oncology 2021, 11(771).
5. X Wang, B Zhang, Q He, Y Kong, Z Dai, H Meng, F Huang, S Zhang, Y Zhu, X Tan, X Zhen: Rectum Protection by Rectal Gel Injection in Cervical Cancer Brachytherapy: A Dosimetric Study via Deformable Surface Dose Accumulation and Machine-Learning-Based Discriminative Modeling. Frontiers in Oncology 2021, 11(1265).
6. L Wang, T Mo, X Wang, W Chen, Q He, X Li, S Zhang, R Yang, J Wu, X Gu, J Wei, P Xie, L Zhou, X Zhen: A hierarchical fusion framework to integrate homogeneous and heterogeneous classifiers for medical decision-making. Knowledge-Based Systems 2021, 212:106517.
7. S Lai, L Sun, J Wu, R Wei, S Luo, W Ding, X Liu, R Yang, X Zhen: Multiphase Contrast-Enhanced CT-Based Machine Learning Models to Predict the Fuhrman Nuclear Grade of Clear Cell Renal Cell Carcinoma. Cancer Management and Research 2021, 13:999-1008.
8. L Wang, C Zheng, W Chen, Q He, X Li, S Zhang, G Qin, W Chen, J Wei, P Xie, L Zhou, X Wang, X Zhen: Multi-path synergic fusion deep neural network framework for breast mass classification using digital breast tomosynthesis. Phys Med Biol 2020, 65(23):235045.
9. A Zhong, B Li, N Luo, Y Xu, L Zhou, X Zhen: Image Restoration for Low-Dose CT via Transfer Learning and Residual Network. IEEE Access 2020, 8:112078-112091.
10. Q He, X Li, DWN Kim, X Jia, X Gu, X Zhen, L Zhou: Feasibility study of a multi-criteria decision-making based hierarchical model for multi-modality feature and multi-classifier fusion: Applications in medical prognosis prediction. Information Fusion 2020, 55:207-219.
11.R Yang, J Wu, L Sun, S Lai, Y Xu, X Liu, Y Ma, X Zhen: Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat. Eur Radiol 2020, 30(2):1254-1263.
12. X Li, G Qin, Q He, L Sun, H Zeng, Z He, W Chen, X Zhen, L Zhou: Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification. Eur Radiol 2020, 30(2):778-788.
13. Q Jia, Y Li, A Wu, F Guo, M Qi, Y Mai, F Kong, X Zhen, L Zhou, T Song: OAR Dose Distribution Prediction and gEUD Based Automatic Treatment Planning Optimization for Intensity Modulated Radiotherapy. IEEE Access 2019, 7:141426-141437.
14. H Chen, W Lu, M Chen, L Zhou, R Timmerman, D Tu, L Nedzi, Z Wardak, S Jiang, X Zhen, X Gu: A recursive ensemble organ segmentation (REOS) framework: application in brain radiotherapy. Phys Med Biol 2019, 64(2):025015.
15. H Chen, M Chen, W Lu, B Zhao, S Jiang, L Zhou, N Kim, A Spangler, A Rahimi, X Zhen, X Gu: Deep-learning based surface region selection for deep inspiration breath hold (DIBH) monitoring in left breast cancer radiotherapy. Phys Med Biol 2018, 63(24):245013.
16. J Chen, H Chen, Z Zhong, Z Wang, B Hrycushko, L Zhou, S Jiang, K Albuquerque, X Gu, X Zhen: Investigating rectal toxicity associated dosimetric features with deformable accumulated rectal surface dose maps for cervical cancer radiotherapy. Radiation Oncology 2018, 13(1):125.
17. C Wang, Y Liao, H Chen, X Zhen, J Li, Y Xu, L Zhou: Influence of tube potential on quantitative coronary plaque analyses by low radiation dose computed tomography: a phantom study. Int J Cardiovasc Imaging 2018.
18. H Chen, Z Zhong, Y Yang, J Chen, L Zhou, X Zhen, X Gu: Internal Motion Estimation by Internal-external Motion Modeling for Lung Cancer Radiotherapy. Scientific Reports 2018, 8(1):3677.
19. X Zhen, J Chen, Z Zhong, B Hrycushko, L Zhou, S Jiang, K Albuquerque, X Gu: Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study. Phys Med Biol 2017, 62(21):8246-8263.
20. X Zhen, B Zhao, Z Wang, R Timmerman, A Spangler, N Kim, A Rahimi, X Gu: Comprehensive target geometric errors and margin assessment in stereotactic partial breast irradiation. Radiation Oncology 2017, 12(1):151.
21. Y Liao, L Wang, X Xu, H Chen, J Chen, G Zhang, H Lei, R Wang, S Zhang, X Gu, X Zhen, L Zhou: An anthropomorphic abdominal phantom for deformable image registration accuracy validation in adaptive radiation therapy. Med Phys 2017, 44(6):2369-2378.
22. Y Liu, S Stojadinovic, B Hrycushko, Z Wardak, S Lau, W Lu, Y Yan, SB Jiang, X Zhen, R Timmerman, L Nedzi, X Gu: A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery. PLOS ONE 2017, 12(10):e0185844.
23. X Li, Y Zhang, Y Shi, S Wu, Y Xiao, X Gu, X Zhen, L Zhou: Comprehensive evaluation of ten deformable image registration algorithms for contour propagation between CT and cone-beam CT images in adaptive head & neck radiotherapy. PLoS One 2017, 12(4):e0175906.
24. YL Liao, HB Chen, LH Zhou, X Zhen: Construction of an anthropopathic abdominal phantom for accuracy validation of deformable image registration. Technology and health care : official journal of the European Society for Engineering and Medicine 2016, 24 Suppl 2:S717-723.
25. X Li, YY Zhang, YH Shi, LH Zhou, X Zhen: Evaluation of deformable image registration for contour propagation between CT and cone-beam CT images in adaptive head and neck radiotherapy. Technol Health Care 2016, 24 Suppl 2:S747-755.
26. H Chen, Z Zhong, Y Liao, A Pompos, B Hrycushko, K Albuquerque, X Zhen, L Zhou, X Gu: A non-rigid point matching method with local topology preservation for accurate bladder dose summation in high dose rate cervical brachytherapy. Phys Med Biol 2016, 61(3):1217-1237.
27. Y Xiao, LH Zhou, X Zhen: FISER: Feature Image Space Enhanced Random Walker Algorithm for Brain Tumor Segmentation in Multimodal MR Images. J Med Imag Health In 2015, 5(8):1977-1981.
28. X Zhen, H Chen, H Yan, L Zhou, LK Mell, CM Yashar, S Jiang, X Jia, X Gu, L Cervino: A segmentation and point-matching enhanced efficient deformable image registration method for dose accumulation between HDR CT images. Phys Med Biol 2015, 60(7):2981-3002.
29. H Chen, X Zhen, X Gu, H Yan, L Cervino, Y Xiao, L Zhou: SPARSE: Seed Point Auto-Generation for Random Walks Segmentation Enhancement in medical inhomogeneous targets delineation of morphological MR and CT images. J Appl Clin Med Phys 2015, 16(2):387-402.
30. SY Wu, HW Li, HL Qi, YB Luo, X Zhen, Y Xu, LH Zhou: A Practical Geometric Calibration Method of Cone-Beam CT System Using Simple Handmade Phantom. Journal of Medical Imaging and Health Informatics 2015, 5(8):1915-1920.
31. H Yan, X Zhen, M Folkerts, Y Li, T Pan, L Cervino, SB Jiang, X Jia: A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging. Med Phys 2014, 41(7):071903.
32. N Li, M Zarepisheh, A Uribe-Sanchez, K Moore, Z Tian, X Zhen, YJ Graves, Q Gautier, L Mell, L Zhou, X Jia, S Jiang: Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs. Phys Med Biol 2013, 58(24):8725-8738.
33. X Zhen, H Yan, L Zhou, X Jia, SB Jiang: Deformable image registration of CT and truncated cone-beam CT for adaptive radiation therapy. Phys Med Biol 2013, 58(22):7979-7993.
34. X Zhen, X Gu, H Yan, L Zhou, X Jia, SB Jiang: CT to cone-beam CT deformable registration with simultaneous intensity correction. Phys Med Biol 2012, 57(21):6807-6826.
35. H Yan, X Zhen, L Cerviño, SB Jiang, X Jia: Progressive cone beam CT dose control in image-guided radiation therapy. Medical Physics 2013, 40(6):060701.
