Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …

Surgical decisions are informed by aligning rapid portable 2D intraoperative images (eg X-
rays) to a high-fidelity 3D preoperative reference scan (eg CT). However 2D/3D registration …

The 2D/3D rigid registration between preoperative 3D CT and intraoperative 2D X-ray is a
crucial step in minimally invasive pelvic surgery. The deep learning-based 2D/3D …

2D-3D registration of native anatomy in dynamic stereo-radiography is a fundamental task in
orthopaedics methods that facilitates understanding of joint-level movement. Registration is …

Abstract Deep learning-based 3D/2D surgical navigation registration techniques achieved
excellent results. However, these methods are limited by the occlusion of surgical equipment …

A robust and efficient optimization-based 2D/3D registration framework is crucial for the
navigation system of orthopedic surgical robots. It can provide precise position information of …

Accurate vessel segmentation from X-ray Angiography (XA) is essential for various medical
applications, including diagnosis, treatment planning, and image-guided interventions …

During Endovascular aneurysm repair (EVAR) procedures, surgeons always require several
views of vessel structures to accurately assess the size, shape, and location of the …

Accurate 2D/3D rigid registration between X-ray and CT images is crucial for orthopedic
surgical navigation. However, existing learning-based methods often result in suboptimal …

Aligning 2D ultrasound images with 3D CT scans of the liver holds significant clinical value
in enhancing diagnostic precision, surgical planning, and treatment delivery. Conventional …