Pose Estimation of 2D Ultrasound Probe from Ultrasound Image Sequences Using CNN and RNN

Kanta Miura, Koichi Ito, Takafumi Aoki, Jun Ohmiya, Satoshi Kondo

研究成果: 書籍の章/レポート/Proceedings会議への寄与査読

4 被引用数 (Scopus)

抄録

In this paper, we propose an ultrasound (US) probe pose estimation method only from US image sequences using deep learning for volume reconstruction. The proposed method employs the combination of convolutional neural network (CNN) and recurrent neural network (RNN) to estimate the US probe pose in light of the long-term temporal information of US image sequences. The features extracted by CNN are input to RNN to estimate the relative and absolute pose of the US probe. Through a set of experiments using US image sequence datasets with ground-truth pose measured by an optical tracking system, we demonstrate that the proposed method exhibits the efficient performance on US probe pose estimation and volume reconstruction compared with the conventional method.

本文言語英語
ホスト出版物のタイトルSimplifying Medical Ultrasound - Second International Workshop, ASMUS 2021, Held in Conjunction with MICCAI 2021, Proceedings
編集者J. Alison Noble, Stephen Aylward, Alexander Grimwood, Zhe Min, Su-Lin Lee, Yipeng Hu
出版社Springer Science and Business Media Deutschland GmbH
ページ96-105
ページ数10
ISBN(印刷版)9783030875824
DOI
出版ステータス出版済み - 2021
イベント2nd International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2021 held in conjunction with 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021 - Strasbourg, フランス
継続期間: 2021 9月 272021 9月 27

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12967 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議2nd International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2021 held in conjunction with 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021
国/地域フランス
CityStrasbourg
Period21/9/2721/9/27

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