U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …

The segmentation of liver blood vessels is of major importance as it is essential for
formulating diagnoses, planning and delivering treatments, as well as evaluating the results …

Prostate cancer biopsy benefits from accurate fusion of transrectal ultrasound (TRUS) and
magnetic resonance (MR) images. In the past few years, convolutional neural networks …

Multi-modal registration is a required step for many image-guided procedures, especially
ultrasound-guided interventions that require anatomical context. While a number of such …

Purpose Despite extensive preoperative imaging, intraoperative localization of liver lesions
after systemic treatment can be challenging. Therefore, an image-guided navigation setup is …

Laparoscopic Ultrasound (LUS) is recommended as a standard-of-care when performing
laparoscopic liver resections as it images sub-surface structures such as tumours and major …

Deep learning has enabled significant improvements in the accuracy of 3D blood vessel
segmentation. Open challenges remain in scenarios where labeled 3D segmentation maps …

Abstract Purpose: Registration of Laparoscopic Ultrasound (LUS) to a pre-operative scan
such as Computed Tomography (CT) using blood vessel information has been proposed as …

Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis
and vessel segmentation. This paper presents a survey of techniques and algorithms for …

Registration of multi-modality images is necessary for the assessment of liver disease. In this
work, we present an image registration workflow which is designed to achieve reliable …