英文代表性著作:
1. Zhang L#, Jia N#, Han L, Yang L, Xu W, Chen W*. Comparative analysis of imaging and pathology features of mucinous carcinoma of the breast, Clinical Breast Cancer, 2015, 15(2):147-54. (JCR3区,IF=2.647)(通讯作者)
2. Qin, G#,Cai, Y#,Long, J,Zeng, H,Xu, W,Li, Y,Liu, M,Zhang, H,He, Z L,Chen, W G*,Cathepsin L is involved in proliferation and invasion of breast cancer cells, Neoplasma, 2016, 63(1):30-36. (JCR 4区,IF=1.721)(通讯作者)
3. Zhang,L(#), Qin,G (#), He,Z, Chen,W*, Yang,L*,The mammography and MRI manifestations of adenomyoepithelioma of the breast, Clinical Radiology, 2016, 71(3): 235-243(JCR 3区,IF=2.118)(共同通讯作者2/2)
4. Jiang L#, Chen WG#, Geng QS#.The cardiothoracic ratio:a neglected preoperative risk-stratified method for patients with rheumatic heart disease undergoing valve replacement surgery, European Journal of Cardio-Thoracic Surgery 00(2018)1-7. (中科院3区,JCR2区,IF:3.486)(共同第一作者2/3)
5. Duan X#, Qin G#, Ling Q, Wang S, Xu Z, Zeng H, Li B, Chen W, Zhou L*, Xu Y*, Matching Corresponding Regions of Interest on Cranio-caudal and Medio-lateral Oblique View Mammograms.IEEE Access, 2019, 7: 31586-31597 (中科院3区,JCR1区,IF:3.476)(8/10)
6. Tianyu Shen#, Chao Gou*, Fei-Yue Wan#, Zilong He, Weiguo Chen*, Learning from adversarial medical images for X-ray breast mass segmentation,Computer Methods and Programs in Biomedicine,2019.105012 (中科院2区,JCR 1区 IF: 7.027)(共同通讯作者2/2)
7. Luo Z, Chen W*, Shen X, Qin G, Yuan J, Hu B, et al. CT and MRI features of calvarium and skull base osteosarcoma (CSBO). Br J Radiol 2020; 93: 20190653. (JCR 3区 IF:2.196) (共同通讯作者2/2)
8. Zhendong Luo, Weiguo Chen*, Xinping Shen, Genggeng Qin, Jianxiang Yuan, Biying Hu, Jianxun Lyu, Chanjuan Wen and Weimin Xu, Head and neck osteosarcoma: CT and MR imaging features, Dentomaxillofacial Radiology (2019) 48, 20190202 . (JCR 3区 IF:2.419)(通讯作者)
9. Yangling Hu, Weimin Xu, Hui Zeng, Zilong He, Xiao Lu, Daming Zuo, Genggeng Qin*, Weiguo Chen*, OXPHOS-dependent metabolic reprogramming prompts metastatic potential of breast cancer cells under osteogenic differentiation, British journal of cancer.2020,123(11): 1644-1655. (中科院分区:2区,JCR 1区 IF:9.082)(共同通讯作者1/2)
10. Le Ma, Xiaojia Lin, Bingjia Lai, Wenshang Wang, Yuxing Cai, Weiguo Chen*, Genggeng Qin*, Additive value of exposure parameters for breast cancer diagnosis in digital mammography, European Radiology. 2020,31(4):2539-2547 (中科院分区:2区,JCR 1区 IF:7.034)(共同通讯作者2/2)
11. Yue Li#, Zilong He#, Yao Lu, Xiangyuan Ma, Yanhui Guo, Zheng Xie, Zeyuan Xu, Weiguo Chen *, Haibin Chen *, Deep Learning in Mammary Glands Distiribution for Architectural Distortion Detection in Digital Breast Tomosynthesis, Physics in Medicine & Biology. 2021 Jan 30;66(3):035028. (中科院分区:3区,JCR 2区 IF:3.609)(共同通讯作者2/2)
12. Le Ma, Yuxing Cai, Xiaojia Lin, Zilong He, Hui Zeng, Weiguo Chen*, and Genggeng Qin, Association of the Differences in Average Glandular Dose with Breast Cancer Risk, Hindawi BioMed Research International,2020. (中科院分区:3区,JCR 3区 IF:2.276)(共同通讯作者2/2)
13. Xu W#, Zheng B#, Chen W, Wen C, Zeng H, He Z, Qin G*, Li Y*. Can the delayed phase of quantitative contrast-enhanced mammography improve the diagnostic performance on breast masses? Quant Imaging Med Surg 2021;11(8):3684-3697.(中科院分区:3区,JCR 2区,IF=4.63)
14. Pan D#, Liu R#, Zheng B, Yuan J, Zeng H, He Z, Luo Z, Qin G*, Chen W*. Using Machine Learning to Unravel the Value of Radiographic Features for the Classification of Bone Tumors. Biomed Res Int, 2021;2021:8811056.(JCR 3区,IF=3.246)(中科院分区:3区,共同通讯作者1/2)
15. Zheng B#, Cai Y, Zeng F, Lin M, Zheng J, Chen W, Qin G*, Guo Y*. An Interpretable Model-Based Prediction of Severity and Crucial Factors in Patients with COVID-19. Biomed Res Int. 2021; 2021:8840835(中科院分区:3区,JCR 3区,IF=2.276)
16. Liu R#, Pan D#, Xu Y, Zeng H, He Z, Lin J, Zeng W, Wu Z, Luo Z, Qin G*, Chen W*. A deep learning-machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors. Eur Radiol. 2021,32(2): 1371-1383(中科院分区:2区,JCR 1区,IF= 7.034)(共同通讯作者1/2)
17. Ma M#, Liu R#, Wen C, Xu W, Xu Z, Wang S, Wu J, PanD, ZhengB, Qin G*, Chen W*. Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms. Eur Radiol. 2021, 32(3): 1652-1662(中科院分区:2区,JCR 1区,IF= 7.034)(共同通讯作者1/2)
18. Jiefang Wu#, Weiguo Chen#, Fengxia Zeng, Le Ma, Weimin Xu, Wei Yang*, Genggeng Qin*. Improved detection of solitary pulmonary nodules on radiographs compared with deep bone suppression imaging. Quant Imaging Med Surg 2021;11(10):4342-4353. (中科院分区:3区,JCR分区:Q2,IF:4.63)(共同第一作者2/2)
19. Li Y#; Wang K#; Chen Y; Cai J; Qin X; Lu A; Guan D*; Qin G*; Chen W*. A system pharmacology model for decoding the synergistic mechanisms of compound kushen injection in treating breast cancer. Frontiers in Pharmacology, 12:723147.(中科院分区:2区,JCR分区:Q1,IF5.988)(共同通讯作者1/3)
20. Zilong He#, Yue Li#, Weixiong Zeng#, Weimin Xu, Jialing Liu, Xiangyuan Ma, Jun Wei, Hui Zeng, Zeyuan Xu, Sina Wang, Chanjuan Wen, Jiefang Wu, Chenya Feng, Mengwei Ma, Genggeng Qin*, Yao Lu* and Weiguo Chen*. Can a computer-aided mass diagnosis model based on perceptive features learned from quantitative mammography radiology report improve junior radiologists’ diagnosis performance? An observer study. FRONTIERS IN ONCOLOGY. 2021,11:773389. (中科院分区:3区,JCR分区:Q2,IF:5.738) (共同通讯作者1/3)
21. Wen C J, Xu W M, Qin G G, Zeng H, He Z L, Wang S N, Xu Z Y, Ma M W, Luo Z D, Chen W G, Pure and Mixed Tubular Carcinoma of the Breast: Mammographic Features, Clinicopathological Characteristics and Prognostic Analysis. TECHNOLOGY IN CANCER RESEARCH & TREATMENT,2021,20(中科院分区:4区,JCR分区:Q3,IF:2.876)(通讯作者)
22. Ma L, Liu H, Lin X J, Cai Y X, Zhang L, Chen W G, Qin G G, Lesion-specific exposure parameters for breast cancer diagnosis on digital breast tomosynthesis and full-field digital mammography. BIOMEDICAL SIGNAL PROCESSING AND CONTROL,2022,77(中科院分区:3区,JCR分区:Q2,IF:5.076)(共同通讯)
23. Jiang G, Wei J, Xu Y, He Z, Zeng H, Wu J, Qin G, Chen W, Lu Y, Synthesis of Mammogram From Digital Breast Tomosynthesis Using Deep Convolutional Neural Network With Gradient Guided cGANs. IEEE TRANSACTIONS ON MEDICAL IMAGING,2021,40(8):2080-2091(中科院分区:1区,JCR分区:Q1,IF:11.037)(共同通讯)
中文代表性著作:
1. 汪思娜,秦耿耿,曾辉,徐泽园,徐维敏,文婵娟,潘德润,陈卫国. 几何模型匹配乳腺头足位与内外斜位X线片所示病灶[J]. 中国医学影像技术,2022,38(11):1636-1641. DOI:10.13929/j.issn.1003-3289.2022.11.009.
2. 刘家玲,何子龙,陈卫国.人工智能技术在乳腺结构扭曲检出中的研究进展[J/OL].国际医学放射学杂志:1-5[2022-09-20].DOI:10.19300/j.2022.Z19814.
3. 徐维敏,郑博文,潘德润,文婵娟,汪思娜,曾辉,何子龙,秦耿耿,陈卫国. CESM量化特征联合形态学对BI-RADS 3~5类乳腺单发肿块的诊断价值[J]. 肿瘤影像学,2022,31(2):146-153. DOI:10.19732/j.cnki.2096-6210.2022.02.007.
4. 徐维敏,郑博文,秦耿耿,文婵娟,汪思娜,徐泽园,吴杰芳,陈卫国. 对比增强能谱乳腺X线摄影量化参数联合强化特点鉴别乳腺良、恶性肿块[J]. 中国医学影像技术,2022,38(7):1023-1028. DOI:10.13929/j.issn.1003-3289.2022.07.014.
5. 冯晨雅,范惟,罗振东,等. 骨外粘液样软骨肉瘤的病理与影像学特点[J]. 分子影像学杂志,2022,45(4):470-474. DOI:10.12122/j.issn.1674-4500.2022.04.02.
6. 黄国慈,曾凤霞,潘德润,等. 增强CT影像组学模型可术前评估甲状腺乳头状癌颈部中央区淋巴结转移[J]. 分子影像学杂志,2022,45(5):643-647. DOI:10.12122/j.issn.1674-4500.2022.05.03.
7. 马乐,林晓佳,曾辉,郭绮晴,蔡裕兴,陈卫国.数字化断层融合(DBT)与全视野数字X线摄影(FFDM)引导乳腺病灶定位对比[J].放射学实践,2021,36(06):742-746.
8. 冯晨雅,秦耿耿,陈卫国.乳腺肿块影像学分割技术现状及进展[J].国际医学放射学杂志,2021,44(03):330-335.
9. 张雅娟,曾凤霞,陈卫国,秦耿耿.基于2015版尘肺病诊断标准影像报告及诊断分期的一致性研究[J].实用医学杂志,2021,37(06):797-801.
10. 吴杰芳,秦耿耿,童凯,陈卫国.肩胛骨肿瘤的临床及影像学分析[J].医学影像学杂志,2021,31(02):317-321.
11. 林淑仪,熊小丽,黄安红,徐维敏,文婵娟,马乐,蔡裕兴,陈卫国.对比增强乳腺X线摄影平均腺体剂量与乳腺病变的相关性[J].分子影像学杂志,2021,44(01):31-35.
12. 马梦伟,秦耿耿,徐维敏,刘仁懿,文婵娟,曾辉,陈卫国.基于X线及超声乳腺影像报告和数据系统构建机器学习模型预测乳腺癌分子分型[J].中国医学影像技术,2020,36(12): 1814-1819.
13. 曾凤霞,陈卫国,秦耿耿.人工智能技术在肝纤维化定量评价中的研究进展[J].国际医学放射学杂志,2020,43(05):578-581.
14. 曾辉,陈卫国,徐泽园,马梦伟,文婵娟,徐维敏.不同分子分型原发乳腺癌临床病理特征及X线、超声表现:140例23~35岁患者[J].分子影像学杂志,2020,43(03):387-393.
15. 马梦伟,秦耿耿,陈卫国.影像组学在乳腺癌分子分型中的应用现状及研究进展[J].国际医学放射学杂志,2020,43(04):452-456.
16. 徐泽园,曾辉,秦耿耿,徐维敏,陈卫国.基于第5版乳腺影像报告和数据系统方法评价乳腺密度的一致性研究[J].肿瘤影像学,2020,29(03):235-240.
17. 胡仰玲,曾辉,何子龙,徐维敏,秦耿耿,陈卫国.钙化型乳腺癌的分子分型特点及其预后分析[J].实用医学杂志,2020,36(10):1354-1359.
18. 吴杰芳,秦耿耿,阳维,贾铭,马乐,陈卫国,文婵娟.深度卷积网络骨抑制技术对孤立性肺结节诊断效能的研究[J].医学影像学杂志,2020,30(04):611-616.
19. 林晓佳,马乐,蔡裕兴,陈卫国.基于临床信息的logistic回归模型在乳腺影像报告和数据系统4类中对病灶良恶性的鉴别价值[J].肿瘤影像学,2020,29(02):85-89.
20. 秦耿耿,曾凤霞,陈卫国,郭怡.COVID-19疫情下影像科室的应急管理策略[J].分子影像学杂志,2020,43(02):278-281.
21. 马立超,许乙凯,文戈,陈卫国,陈燕萍,张春辉,刘杰,吴元魁,李晓丹,杨洪波.“医学影像学”在线教学的实践及经验[J].高校医学教学研究(电子版),2020,10(02):51-55.
22. 曾凤霞,蔡勇,汪思娜,曾辉,陈卫国,秦耿耿.X线与CT在新型冠状病毒肺炎诊断中的应用[J].广东医学,2020,41(07):656-660.
23. 郑博文,陈卫国,秦耿耿.人工智能在功能与分子影像学的研究进展[J].分子影像学杂志,2020,43(01):1-6.
24. 文婵娟,徐维敏,曾辉,何子龙,吴杰芳,徐泽园,汪思娜,秦耿耿,陈卫国.对比增强X线摄影对乳腺可疑病变的诊断价值[J]. 中华放射学杂志,2019,53(09):737-741.
25. 周俊,赵亮,蔡裕兴,陈卫国,唐浩.骨原发性少见病理亚型软骨肉瘤的病理与影像学特征[J].疑难病杂志,2019,18(05):515-518+542.
26. 徐泽园,秦耿耿,陈卫国.致密型乳腺影像筛查技术及研究进展[J].国际医学放射学杂志,2019,42(03):312-316.
27. 汪思娜,徐维敏,秦耿耿,文婵娟,曾辉,何子龙,徐泽园,陈卫国.乳腺X线摄影及超声鉴别诊断乳腺叶状肿瘤与纤维腺瘤[J].中国医学影像技术,2019,35(03):362-366.
28. 潘德润,秦耿耿,陈卫国.基于深度学习的人工智能技术在乳腺癌筛查及影像诊断中的应用进展[J].国际医学放射学杂志,2019,42(01):12-15.
29. 徐维敏,李颖嘉,文婵娟,曾辉,秦耿耿,何子龙,陈卫国.青年乳腺癌X线与病理、分子分型的对照分析[J].影像诊断与介入放射学,2018,27(06):433-439.
30. 唐水英,唐浩,何子龙,杜钢,陈卫国.淋巴结外Rosai-Dorfman病的影像学分析[J].临床放射学杂志,2018,37(12):1985-1988.
31. 何子龙,吕闻冰,秦耿耿,廖昕,徐维敏,文婵娟,曾辉,陈卫国.基于数字乳腺断层摄影图像纹理特征提取的单纯肿块型病变的深度学习分类模型构建的可行性[J].中华放射学杂志,2018,52(09):668-672.
专家共识:
1. 数字乳腺X线断层摄影检查技术、诊断规范专家组. 数字乳腺X线断层摄影检查技术及其诊断应用规范专家共识[J]. 循证医学,2021,21(3):145-150.