Out-of-Plane Motion Detection System Using Convolutional Neural Network for US-guided Radiofrequency Ablation Therapy

Ryosuke Kondo, Norihiro Koizumi, Yu Nishiyama, Naoki Matsumoto, Kazushi Numata

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Radiofrequency ablation therapy support system aims to display the true tumor position by tracking the tumor at the time of treatment. As a major cause of the error, the tumor moves in the direction which is perpendicular to the scan plane of the ultrasound image. Therefore, in the proposed method, the six-axis movement amount is estimated from two ultrasound images by a convolution neural network. By this method, we estimated the amount of movement in the direction perpendicular to the ultrasound image plane and aimed at tracking more accurately. We conducted an experiment to estimate the probe movement amount with respect to the liver phantom and confirmed the certain effectiveness of this method.

Original languageEnglish
Title of host publication2018 15th International Conference on Ubiquitous Robots, UR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages729-731
Number of pages3
ISBN (Print)9781538663349
DOIs
Publication statusPublished - 20 Aug 2018
Event15th International Conference on Ubiquitous Robots, UR 2018 - Honolulu, United States
Duration: 27 Jun 201830 Jun 2018

Publication series

Name2018 15th International Conference on Ubiquitous Robots, UR 2018

Conference

Conference15th International Conference on Ubiquitous Robots, UR 2018
Country/TerritoryUnited States
CityHonolulu
Period27/06/1830/06/18

Fingerprint

Dive into the research topics of 'Out-of-Plane Motion Detection System Using Convolutional Neural Network for US-guided Radiofrequency Ablation Therapy'. Together they form a unique fingerprint.

Cite this