Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …

Sensorless freehand 3D ultrasound (US) reconstruction based on deep networks shows
promising advantages, such as large field of view, relatively high resolution, low cost, and …

Freehand 3D ultrasound (US) has important clinical value due to its low cost and
unrestricted field of view. Recently deep learning algorithms have removed its dependence …

Transrectal ultrasound is commonly used for guiding prostate cancer biopsy, where 3D
ultrasound volume reconstruction is often desired. Current methods for 3D reconstruction …

Ultrasound (US) imaging is a popular tool in clinical diagnosis, offering safety, repeatability,
and real-time capabilities. Freehand 3D US is a technique that provides a deeper …

3D ultrasound reconstruction has important application value in clinical diagnosis. To obtain
the spatial relationships between ultrasound images in reconstruction tasks, especially the …

In the medical field, 3D ultrasound reconstruction can visualize the internal structure of
patients, which is very important for doctors to carry out correct analyses and diagnoses …

In recent years, deep learning algorithms have become the standard approach for analyzing
fetal images obtained through ultrasound technology. This chapter surveys the most up-to …

Objective: The accuracy of biopsy targeting is a major issue for prostate cancer diagnosis
and therapy. However, navigation to biopsy targets remains challenging due to the …

Three-dimensional (3D) freehand ultrasound (US) reconstruction without a tracker can be
advantageous over its two-dimensional or tracked counterparts in many clinical applications …