The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2023
Session ID : 2P1-C03
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Puncture Needle Detection in Volume CT Images Using Both Deep Learning and Gradient Calculation
*Takayuki MATSUNOKOTARO MayumiTakaaki TANAKASeiya KOBAYASHINozomu FUJITSUKAYuichiro TODATetsushi KAMEGAWATakao HIRAKI
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Abstract

We have developed a CT guided needle puncture robot (Zerobot) to assist in interventional radiology surgery. Currently, Zerobot is operated remotely, and the next goal is to perform automatic needle puncture surgery. There is a challenge that automatic detection of puncture needle from CT images for first step of automatic puncture surgery. Because there is the case that the form of puncture needle is curved, it is necessary to detect the needle from CT image instead of estimating the needle position from arm of Zerobot. First, the method detects ROI with ResNet. Next, the gradient of the CT value is calculated for each pixel in the ROI, and a linear approximation is performed for to detect the needle shape. Images from animal experiments were used to evaluate the learner and image processing. We confirmed that the proposed method can detect needles in a single image and in multiple images.

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© 2023 The Japan Society of Mechanical Engineers
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