There is a large body of literature linking anatomic and geometric characteristics of kidney
tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors …

This paper presents a review of automated image registration methodologies that have been
used in the medical field. The aim of this paper is to be an introduction to the field, provide …

Image registration is a fundamental medical image analysis task, and a wide variety of
approaches have been proposed. However, only a few studies have comprehensively …

Despite advances in data augmentation and transfer learning, convolutional neural
networks (CNNs) difficultly generalise to unseen domains. When segmenting brain scans …

International challenges have become the standard for validation of biomedical image
analysis methods. Given their scientific impact, it is surprising that a critical analysis of …

A retrospective view on the past two decades of the field of medical image registration is
presented, guided by the article “A survey of medical image registration”(Maintz and …

Medical image registration is an important task in medical image processing. It refers to the
process of aligning data sets, possibly from different modalities (eg, magnetic resonance …

The registration of images is a task that is at the core of many applications in computer
vision. In computational neuroimaging where the automated segmentation of brain …

Medical images acquired from different modalities give rise to many practical problems in
image registration. Intensity-based registration techniques have been increasingly used in …

BACKGROUND: Stereoelectroencephalography (SEEG) methodology, originally developed
by Talairach and Bancaud, is progressively gaining popularity for the presurgical invasive …