@inproceedings{1a1eb20b26c64182a3b6b165f36ac5b1,
title = "Probe localization from ultrasound image sequences using deep learning for volume reconstruction",
abstract = "We propose a probe localization method only from ultrasound (US) image sequences using deep learning for three-dimensional (3D) US image reconstruction. The proposed method employs a convolutional neural network (CNN) to estimate the motion of the probe from two US images. Our CNN architecture consists of two parts: inplane and out-of-plane probe motion estimation. Two loss functions are introduced to guarantee the consistency of estimated motion of the probe between multiple frames. Through experiments, we demonstrate that the proposed method exhibits efficient performance on probe localization compared with the conventional method.",
keywords = "CNN, probe localization, ultrasound, volume reconstruction",
author = "Kanta Miura and Koichi Ito and Takafumi Aoki and Jun Ohmiya and Satoshi Kondo",
note = "Publisher Copyright: {\textcopyright} 2021 SPIE.; International Forum on Medical Imaging in Asia 2021, IFMIA 2021 ; Conference date: 24-01-2021 Through 26-01-2021",
year = "2021",
doi = "10.1117/12.2590805",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Ruey-Feng Chang",
booktitle = "International Forum on Medical Imaging in Asia 2021",
}