عنوان انگلیسی مقاله:
Surgical Phase Recognition Method with a Sequential Consistency for CAOS-AI Navigation System
ترجمه فارسی عنوان مقاله:
روش تشخیص مرحله جراحی با یک سازگاری متوالی برای سیستم ناوبری CAOS-AI
IEEE - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech);2020; ; ;10.1109/LifeTech48969.2020.1570619203
Shoichi Nishio , Belayat Hossain, Naomi Yagi , Manabu Nii , Takafumi Hiranaka , Syoji Kobashi
The procedure of orthopedic surgery is quite
complicated, and many kinds of equipment have been used.
Operating room nurses who deliver surgical instruments to surgeon
are supposed to be forced to incur a heavy burden. There are some
studies to recognize surgical phase with convolutional neural
network (CNN) in minimally invasive laparoscopic surgery only.
Previously, we proposed a computer-aided orthopedic surgery
(CAOS)-AI navigation system based on CNN. However, the work
propose a method to improve accuracy of phase recognition by
considering temporal dependency of orthopedic surgery video
acquired from surgeon-wearable video camera. The method
estimates current surgical phase by combining both temporal
dependency and convolutional-long-short term memory network
(CNN-LSTM). Experimental results shows a phase recognition
accuracy of 59.9% by the proposed method applied in unicomapartmenatal
knee arthroplasty (UKA).
Keywords: Deep Learning | Computer-aided Orthopaedic Surgery | Operating Room Nurse | Phase Recognition