Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 172-175.doi: 10.11896/JsJkx.190500154
• Computer Graphics & Multimedia • Previous Articles Next Articles
QI Bao-lian1, 3, ZHONG Kun-hua1, 2, 3 and CHEN Yu-wen1, 2, 3
CLC Number:
[1] 徐大华.高科技引领微创外科发展.科技导报,2017,35(11):69-70. [2] 曹晖.人工智能医疗给外科医生带来的挑战、机遇与思考.中国实用外科杂志,2017(12):387-388. [3] JIN Y,DOU Q,CHEN H,et al.SV-RCNet:Workflow recognition from surgical videos using recurrent convolutional network.IEEE Trans.Med.Imaging,2018,37(5):1114-1126. [4] TWINANDA A,YENGERA G,MUTTER D.RSDNet:Lear-ning to Predict Remaining Surgery Duration from Laparoscopic Videos Without Manual Annotations.arXiv:1802.03243v2,2018. [5] LOUKAS C.Video content analysis of surgical procedures.Surgical Endoscopy,2018,32(2):553-568. [6] LI X,URICCHIO T,BALLAN L,et al.Socializing the Semantic Gap:A Comparative Survey on Image Tag Assignment,Refinement,and Retrieval.Acm Computing Surveys,2016,49(1):14. [7] KLANK U,PADOY N,FEUSSNER H.Navab N (2008) Automatic feature generation in endoscopic images.Int J Comput Assist Radiol Surg 3:331-339. [8] BLUM T,FEUSSNER H,NAVAB N.Modeling and segmentation of surgical workflow from laparoscopic video.Lect Notes Comput Sci,2010,6363:400-407. [9] DERGACHYOVA O,BOUGET D,HUAULM A,et al.Automatic data-driven real-time segmentation and recognition of surgical workflow.Int J Comput Assist Radiol Surg,2016,11:1081-1089. [10] TWINANDA A P,SHEHATA S,MUTTER D,et al.EndoNet:a deep architecture for recognition tasks on laparoscopic videos.IEEE Trans Med Imaging,2017,36:86-97. [11] LOUKAS C.Surgical Phase Recognition of Short Video Shots Based on Temporal Modeling of Deep Features.arXiv:1807.07853,2018. [12] LECUN Y,BENGIO Y,HINTON G.Deep learning.Nature,2015,521(7553):436. [13] GENG C,SONG J X.Human Action Recognition based on Convolutional Neural Networks with a Convolutional Auto-Encoder//International Conference on Computer Sciences and Automation Engineering.Atlantis Press,2016. [14] RONNEBERGER O,FISCHER P,BROX T.U-Net:Convolutional Networks for Biomedical Image Segmentation//Medi-cal Image Computing and Computer-Assisted Intervention-MICCAI 2015.Springer International Publishing,2015:234-241. |
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