Image-based navigation is widely considered the next frontier of minimally invasive surgery.
It is believed that image-based navigation will increase the access to reproducible, safe, and …

In this paper, we present a Convolutional Neural Network (CNN) regression approach to
address the two major limitations of existing intensity-based 2-D/3-D registration technology …

Image-based 2D/3D registration is a critical technique for fluoroscopic guided surgical
interventions. Conventional intensity-based 2D/3D registration approa-ches suffer from a …

Methods for deep learning based medical image registration have only recently approached
the quality of classical model-based image alignment. The dual challenge of both a very …

D image registration, which involves aligning two or more images, is a critical step in a
variety of medical applications from diagnosis to therapy. Image registration is commonly …

Accurate two-dimensional to three-dimensional (2-D/3-D) registration of preoperative 3-D
data and intraoperative 2-D x-ray images is a key enabler for image-guided therapy. Recent …

Current approaches for deformable medical image registration often struggle to fulfill all of
the following criteria: versatile applicability, small computation or training times, and the …

Image registration plays an important role in medical image analysis. Conventional
optimization based methods provide an accurate estimation due to the iterative process at …

Minimally invasive and less invasive procedure is becoming more and more common in
medical therapy. Image guidance is an indispensable component in minimally invasive …

We present KeyMorph, a deep learning-based image registration framework that relies on
automatically detecting corresponding keypoints. State-of-the-art deep learning methods for …