Image quality improvement in single plane-wave imaging using deep learning.

In ultrasound image diagnosis, single plane-wave imaging (SPWI), which can acquire ultrasound images at more than 1000 fps, has been used to observe detailed tissue and evaluate blood flow. SPWI achieves high temporal resolution by sacrificing the spatial resolution and contrast of ultrasound images. To improve spatial resolution and contrast in SPWI, coherent plane-wave compounding (CPWC) is used to obtain high-quality ultrasound images, i.

Neural Radiance Field-Inspired Depth Map Refinement for Accurate Multi-View Stereo.

In this paper, we propose a method to refine the depth maps obtained by Multi-View Stereo (MVS) through iterative optimization of the Neural Radiance Field (NeRF). MVS accurately estimates the depths on object surfaces, and NeRF accurately estimates the depths at object boundaries. The key ideas of the proposed method are to combine MVS and NeRF to utilize the advantages of both in depth map estimation and to use NeRF for depth map refinement.

Pose Estimation of Ultrasound Probe Using CNN and RNN with Image Reconstruction Loss.

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.