Voice based Segmentation of Laparoscopic Surgical Tools and its Image Enhancement

Soorva Ram Shimgekar, Preetham Reddy Pathi, S. V
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引用次数: 1

Abstract

With more and more people preferring Laparo-scopic surgeries because of its benefits like smaller scars and being relatively painless in nature, there is immense need to solve the issues the doctors face while performing a Laparoscopic surgery. In this paper we propose a surgical tool segmentation and image enhancement method which can be controlled with a voice based interface. The proposed method solves problems like glare and fogging in addition to segmenting the surgical tools. A voice based interface was used so that the doctor does not have to get distracted while performing the surgery. This method can be helpful to surgeons and can also be helpful in achieving automated surgeries. For image segmentation we use Mask-RCNN and Kaldi Voice Recognition toolkit for the voice based interface. Kaldi toolkit has a great influence on the time taken by the system to understand the query.
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基于语音的腹腔镜手术工具分割及其图像增强
随着越来越多的人喜欢腹腔镜手术,因为它的好处,如更小的疤痕和相对无痛的性质,有巨大的需要解决医生在进行腹腔镜手术时面临的问题。本文提出了一种基于语音接口控制的手术工具分割和图像增强方法。该方法除了对手术工具进行分割外,还解决了眩光和雾化等问题。使用了基于语音的界面,这样医生在进行手术时就不会分心。这种方法可以帮助外科医生,也可以帮助实现自动化手术。对于图像分割,我们使用Mask-RCNN和Kaldi语音识别工具包作为基于语音的接口。Kaldi工具箱对系统理解查询所花费的时间有很大的影响。
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