TY - GEN
T1 - Pose Estimation of Ultrasound Probe Using CNN and RNN with Image Reconstruction Loss
AU - Miura, Kanta
AU - Ito, Koichi
AU - Aoki, Takafumi
AU - Ohmiya, Jun
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - It is necessary to estimate the pose of the probe with high accuracy to reconstruct 3D ultrasound (US) images only from US image sequences scanned by a 1D-array probe. We propose the probe pose estimation method using Convolutional Neural Network (CNN) with training by image reconstruction loss. To calculate the image reconstruction loss, we use the image reconstruction network which consists of an encoder that extracts features from the two US images and a decoder that reconstructs the intermediate US image between the two images. CNN is trained to minimize the image reconstruction loss between the ground-truth image and the reconstructed image. Through experiments, we demonstrate that the proposed method exhibits efficient performance compared with the conventional methods.
AB - It is necessary to estimate the pose of the probe with high accuracy to reconstruct 3D ultrasound (US) images only from US image sequences scanned by a 1D-array probe. We propose the probe pose estimation method using Convolutional Neural Network (CNN) with training by image reconstruction loss. To calculate the image reconstruction loss, we use the image reconstruction network which consists of an encoder that extracts features from the two US images and a decoder that reconstructs the intermediate US image between the two images. CNN is trained to minimize the image reconstruction loss between the ground-truth image and the reconstructed image. Through experiments, we demonstrate that the proposed method exhibits efficient performance compared with the conventional methods.
UR - http://www.scopus.com/inward/record.url?scp=85179638765&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85179638765&partnerID=8YFLogxK
U2 - 10.1109/EMBC40787.2023.10340326
DO - 10.1109/EMBC40787.2023.10340326
M3 - Conference contribution
C2 - 38083044
AN - SCOPUS:85179638765
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
BT - 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023
Y2 - 24 July 2023 through 27 July 2023
ER -