Various imaging artifacts, low signal-to-noise ratio, and bone surfaces appearing several
millimeters in thickness have hindered the success of ultrasound (US) guided computer …

Purpose Automatic bone surfaces segmentation is one of the fundamental tasks of
ultrasound (US)-guided computer-assisted orthopedic surgery procedures. However, due to …

Purpose Ultrasound (US) provides real-time, two-/three-dimensional safe imaging. Due to
these capabilities, it is considered a safe alternative to intra-operative fluoroscopy in various …

Purpose A new algorithm, based on fully convolutional networks (FCN), is proposed for the
automatic localization of the bone interface in ultrasound (US) images. The aim of this paper …

Purpose Precise localization of cystic bone lesions is crucial for osteolytic bone tumor
surgery. Recently, there is a move toward ultrasound imaging over plain radiographs (X …

Due to imaging artifacts and low signal-to-noise ratio in ultrasound images, automatic bone
surface segmentation networks often produce fragmented predictions that can hinder the …

We present a novel method for bone structure segmentation in two-dimensional (2D)
ultrasound (US) images as a precursor to 3D bone surface reconstruction and registration …

Ultrasound bone segmentation is an important yet challenging task for many clinical
applications. Several works have emerged attempting to improve and automate bone …

Ultrasound (US) imaging is a safe alternative to radiography for guidance during minimally
invasive orthopedic procedures. However, ultrasound is challenging to interpret because of …

Artificial Intelligence (AI) in medical image analysis has achieved excellent success in
automatic diagnosis in the same way as clinician, especially in the ultrasound field. In this …