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MURAGAKI Yoshihiro
Department School of Medicine(Tokyo Women's Medical University Hospital), School of Medicine Position Visiting Professor |
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| Language | English |
| Title | Surgical Process Identification System using Machine Learning in Awake Surgery for Brain Tumor |
| Conference | 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech) |
| Conference Type | Nationwide Conferences |
| Presentation Type | Speech |
| Lecture Type | General |
| Publisher and common publisher | ◎NAGAI Tomohiro , SATO Ikuma , FUJINO Yuichi , TAMURA Manabu, MURAGAKI Yoshihiro, MASAMUNE Ken |
| Date | 2019/03/13 |
| Venue (city and name of the country) |
Osaka, Japan |
| Summary | I. Introduction
In brain tumor surgery, a high brain tumor removal rate and post-operative neuroglial complications are important. During surgery for brain tumor, an expert surgeons confirms the brain structure, brain function and location of the brain tumor for each patient. Therefore, the surgical workflow is complicated, surgical process, work contents and duration of surgery vary by case. Hence, it is difficult for young surgeons and surgical staff to understand the surgical process and to predict the next work in awake surgery for brain tumor. The identification and visualization of surgical processes of the expert surgeon, it is possible to support understanding for young surgeons and other surgical staffs. Therefore, we aimed to developed the method for surgical process identification. IEEE Keywords Surgery, Tumors, Feature extraction, Navigation, Microscopy, Hidden Markov models |