| [1] |
DOGRUL B N, KILICCALAN I, ASCI E S, et al. Blunt trauma related chest wall and pulmonary injuries: An overview[J]. Chin J Traumatol,2020,23(3):125-138. doi:10.1016/j.cjtee.2020.04.003 .
|
| [2] |
Expert Panel on Major Trauma Imaging, SHYU J Y, KHURANA B, et al. ACR appropriateness criteria® major blunt trauma[J]. J Am Coll Radiol,2020,17(5S):S160-S174. doi:10.1016/j.jacr.2020.01.024 .
|
| [3] |
AWAIS M, SALAM B, NADEEM N, et al. Diagnostic accuracy of computed tomography scout film and chest X-ray for detection of rib fractures in patients with chest trauma: A cross-sectional study[J]. Cureus,2019,11(1):e3875. doi:10.7759/cureus.3875 .
|
| [4] |
倪伟勇,钱昭军. 肋骨骨折鉴定时间研究[J].刑事技术,2015,40(2):114-117. doi:10.16467/j.1008-3650.2015.02.007 .
|
|
NI W Y, QIAN Z J. Forensic evaluation of the time of rib fracture[J]. Xingshi Jishu,2015,40(2):114-117.
|
| [5] |
吕铭,黄建松,张运阁,等. 薄层螺旋CT扫描在肋骨骨折法医学鉴定中的应用分析[J].中国司法鉴定,2021(1):54-59. doi:10.3969/j.issn.1671-2072.2021.01.007 .
|
|
LÜ M, HUANG J S, ZHANG Y G, et al. Application of thin-slice spiral CT scan in forensic identification of rib fractures[J]. Zhongguo Sifa Jianding,2021(1):54-59.
|
| [6] |
刘才广,莫屈,肖羿,等. 医学影像人工智能在甲状腺癌诊疗中的应用:现状与展望[J].中国普通外科杂志,2024,33(11):1874-1882. doi:10.7659/j.issn.1005-6947.2024.11.014 .
|
|
LIU C G, MO Q, XIAO Y, et al. Applications of medical imaging artificial intelligence in the diagnosis and treatment of thyroid cancer: Current status and future prospects[J]. Zhongguo Putong Waike Zazhi,2024,33(11):1874-1882.
|
| [7] |
黄美莎,张恒,李姝璇,等. 影像组学在法医骨关节损伤鉴定中的应用展望[J].中国法医学杂志,2024,39(1):95-100. doi:10.13618/j.issn.1001-5728.2024.01.016 .
|
|
HUANG M S, ZHANG H, LI S X, et al. Application prospect of radiomics in forensic examination on bone and joint injury[J]. Zhongguo Fayixue Zazhi,2024,39(1):95-100.
|
| [8] |
邱锡鹏. 神经网络与深度学习[M].北京:机械工业出版社,2020:23.
|
|
QIU X P. Neural networks and deep learning[M]. Beijing: China Machine Press,2020:23.
|
| [9] |
ERICKSON B J. Basic artificial intelligence techniques: Machine learning and deep learning[J]. Radiol Clin North Am,2021,59(6):933-940. doi:10.1016/j.rcl.2021.06.004 .
|
| [10] |
DREIZIN D, ZHOU Y, ZHANG Y, et al. Performance of a deep learning algorithm for automated segmentation and quantification of traumatic pelvic hematomas on CT[J]. J Digit Imaging,2020,33(1):243-251. doi:10.1007/s10278-019-00207-1 .
|
| [11] |
RAJAMANI K T, RANI P, SIEBERT H, et al. Attention-augmented U-Net (AA-U-Net) for semantic segmentation[J]. Signal Image Video Process,2023,17(4):981-989. doi:10.1007/s11760-022-02302-3 .
|
| [12] |
BHANDARY S, KUHN D, BABAIEE Z, et al. Investigation and benchmarking of U-Nets on prostate segmentation tasks[J]. Comput Med Imaging Graph,2023,107:102241. doi:10.1016/j.compmedimag.2023. 102241 .
|
| [13] |
ZHOU Z, FU Z, JIA J, et al. Rib fracture detection with dual-attention enhanced U-Net[J]. Comput Math Methods Med,2022,2022:8945423. doi:10.1155/ 2022/8945423 .
|
| [14] |
WANG S, WU D, YE L, et al. Assessment of automatic rib fracture detection on chest CT using a deep learning algorithm[J]. Eur Radiol,2023,33(3):1824-1834. doi:10.1007/s00330-022-09156-w .
|
| [15] |
WANG X, WANG Y. Composite attention residual U-Net for rib fracture detection[J]. Entropy (Basel),2023,25(3):466. doi:10.3390/e25030466 .
|
| [16] |
ZHANG B, JIA C, WU R, et al. Improving rib fracture detection accuracy and reading efficiency with deep learning-based detection software: A clinical evaluation[J]. Br J Radiol,2021,94(1118):20200870. doi:10.1259/bjr.20200870 .
|
| [17] |
YAO L, GUAN X, SONG X, et al. Rib fracture detection system based on deep learning[J]. Sci Rep,2021,11(1):23513. doi:10.1038/s41598-021-03002-7 .
|
| [18] |
白洁,孙晶,程晓光,等. 基于YOLOv3算法的肋骨骨折诊断模型的构建及应用[J].法医学杂志,2023,39(4):343-349,359. doi:10.12116/j.issn.1004-5619.2023.230308 .
|
|
BAI J, SUN J, CHENG X G, et al. Construction and application of rib fracture diagnosis model based on YOLOv3 algorithm[J]. Fayixue Zazhi,2023,39(4):343-349,359.
|
| [19] |
ZHOU Q Q, TANG W, WANG J, et al. Automatic detection and classification of rib fractures based on patients’ CT images and clinical information via convolutional neural network[J]. Eur Radiol,2021,31(6):3815-3825. doi:10.1007/s00330-020-07418-z .
|
| [20] |
EDAMADAKA S, BROWN D W, SWAROOP R, et al. FasterRib: A deep learning algorithm to automate identification and characterization of rib fractures on chest computed tomography scans[J]. J Trauma Acute Care Surg,2023,95(2):181-185. doi:10.1097/TA.0000000000003913 .
|
| [21] |
WU M, CHAI Z, QIAN G, et al. Development and evaluation of a deep learning algorithm for rib segmentation and fracture detection from multicenter chest CT images[J]. Radiol Artif Intell,2021,3(5):e200248. doi:10.1148/ryai.2021200248 .
|
| [22] |
MENG X H, WU D J, WANG Z, et al. A fully automated rib fracture detection system on chest CT images and its impact on radiologist performance[J]. Skeletal Radiol,2021,50(9):1821-1828. doi:10.1007/s00256-021-03709-8 .
|
| [23] |
ZHOU Q Q, HU Z C, TANG W, et al. Precise anatomical localization and classification of rib fractures on CT using a convolutional neural network[J]. Clin Imaging,2022,81:24-32. doi:10.1016/j.clinimag. 2021.09.010 .
|
| [24] |
YANG C, WANG J, XU J, et al. Development and assessment of deep learning system for the location and classification of rib fractures via computed tomography[J]. Eur J Radiol,2022,154:110434. doi:10.1016/j.ejrad.2022.110434 .
|
| [25] |
REN S, HE K, GIRSHICK R, et al. Faster R-CNN: Towards real-time object detection with region proposal networks[J]. IEEE Trans Pattern Anal Mach Intell,2017,39(6):1137-1149. doi:10.1109/TPAMI.2016.2577031 .
|
| [26] |
何俊,王东建,王泽飞,等. 影像检查鉴别肋骨陈旧与新鲜骨折1例[J].中国法医学杂志,2025,40(S1):277-278. doi:10.13618/j.issn.1001-5728.2025.S.149 .
|
|
HE J, WANG D J, WANG Z F, et al. Differentiation between old and fresh rib fractures using imaging examination: A case report[J]. Zhongguo Fayixue Zazhi,2025,40(S1):277-278.
|
| [27] |
ARREDONDO-GÓMEZ E. Treatment of traumatic clavicular pseudoarthrosis with the hunec colchero nail[J]. Acta Ortop Mex,2007,21(2):63-68.
|
| [28] |
吴新宝,姜钰. 陈旧性骨折[J].中华外科杂志,2015,53(6):460-463. doi:10.3760/cma.j.issn.0529-5815.2015.06.014 .
|
|
WU X B, JIANG Y. Old fracture[J]. Zhonghua Waike Zazhi,2015,53(6):460-463.
|
| [29] |
TANG Y, JIN L, JI W, et al. Determining rib fracture age from CT scans with a radiomics-based combined model: A multicenter retrospective study[J]. Insights Imaging,2023,14(1):214. doi:10.1186/s13 244-023-01546-y .
|
| [30] |
JIN L, SUN Y, MA Z, et al. Radiomics-based machine learning for predicting the injury time of rib fractures in gemstone spectral imaging scans[J]. Bioengineering (Basel),2022,10(1):8. doi:10.3390/bioengineering10010008 .
|
| [31] |
BEHESHTIAN E, PUTMAN K, SANTOMARTINO S M, et al. Generalizability and bias in a deep learning pediatric bone age prediction model using hand radiographs[J]. Radiology,2023,306(2):e220505. doi:10.1148/radiol.220505 .
|
| [32] |
IMWINKELRIED E J,杜春鹏(译,李尧(译. 计算机源代码:自动化法庭科技可靠性争议日盛之缘由[J].证据科学,2019,27(4):491-513. doi:10.3969/j.issn.1674-1226.2019.04.009 .
|
|
IMWINKELRIED E J, DU C P transl), LI Y transl). Computer source code: A source of the growing controversy over the reliability of automated forensic techniques[J]. Zhengju Kexue,2019,27(4):491-513.
|
| [33] |
FAN F, LIU H, DAI X, et al. Automated bone age assessment from knee joint by integrating deep learning and MRI-based radiomics[J]. Int J Legal Med,2024,138(3):927-938. doi:10.1007/s00414-023-03148-1 .
|
| [34] |
苏青. 鉴定意见概念之比较与界定[J].法律科学(西北政法大学学报),2016,34(1):154-161. doi:10.16290/j.cnki.1674-5205.2016.01.016 .
|
|
SU Q. A comparative study on definition of forensic appraisal opinion[J]. Falü Kexue (Xibei Zhengfa Da-xue Xuebao),2016,34(1):154-161.
|
| [35] |
TOURNOIS L, TROUSSET V, HATSCH D, et al. Artificial intelligence in the practice of forensic medicine: A scoping review[J]. Int J Legal Med,2024,138(3):1023-1037. doi:10.1007/s00414-023-03140-9 .
|