The impact of machine learning on 2d/3d registration for image-guided interventions: A systematic review and perspective

M Unberath, C Gao, Y Hu, M Judish… - Frontiers in Robotics …, 2021 - frontiersin.org
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 …

Computed tomography: state-of-the-art advancements in musculoskeletal imaging

HA Ibad, C de Cesar Netto, D Shakoor… - Investigative …, 2023 - journals.lww.com
Although musculoskeletal magnetic resonance imaging (MRI) plays a dominant role in
characterizing abnormalities, novel computed tomography (CT) techniques have found an …

Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis

C Gao, BD Killeen, Y Hu, RB Grupp… - Nature Machine …, 2023 - nature.com
Artificial intelligence (AI) now enables automated interpretation of medical images. However,
AI's potential use for interventional image analysis remains largely untapped. This is …

Source-detector trajectory optimization in cone-beam computed tomography: a comprehensive review on today's state-of-the-art

S Hatamikia, A Biguri, G Herl, G Kronreif… - Physics in Medicine …, 2022 - iopscience.iop.org
Cone-beam computed tomography (CBCT) imaging is becoming increasingly important for a
wide range of applications such as image-guided surgery, image-guided radiation therapy …

Known operator learning and hybrid machine learning in medical imaging—a review of the past, the present, and the future

A Maier, H Köstler, M Heisig, P Krauss… - Progress in …, 2022 - iopscience.iop.org
In this article, we perform a review of the state-of-the-art of hybrid machine learning in
medical imaging. We start with a short summary of the general developments of the past in …

Learning human inverse kinematics solutions for redundant robotic upper-limb rehabilitation

D Bedolla-Martinez, Y Kali, M Saad… - … Applications of Artificial …, 2023 - Elsevier
This paper proposes a real-time human inverse kinematics approach based on the
Gaussian Process (GP) to address the open problem of finding appropriate inverse …

Practical part-specific trajectory optimization for robot-guided inspection via computed tomography

F Bauer, D Forndran, T Schromm… - Journal of Nondestructive …, 2022 - Springer
Robot-guided computed tomography enables the inspection of parts that are too large for
conventional systems and allows, for instance, the non-destructive and volumetric …

Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning-A Review

M Amirian, D Barco, I Herzig, FP Schilling - Ieee Access, 2024 - ieeexplore.ieee.org
Deep learning based approaches have been used to improve image quality in cone-beam
computed tomography (CBCT), a medical imaging technique often used in applications such …

Convex optimization algorithms in medical image reconstruction—in the age of AI

J Xu, F Noo - Physics in Medicine & Biology, 2022 - iopscience.iop.org
The past decade has seen the rapid growth of model based image reconstruction (MBIR)
algorithms, which are often applications or adaptations of convex optimization algorithms …

Task-specific trajectory optimisation for twin-robotic x-ray tomography

G Herl, J Hiller, M Thies, JN Zaech… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
With the advent of robotic C-arm computed tomography (CT) systems in medicine and twin-
robotic CT systems in industry, new possibilities for the realisation of complex trajectories for …