8 research outputs found
Augmented Reality and Artificial Intelligence in Image-Guided and Robot-Assisted Interventions
In minimally invasive orthopedic procedures, the surgeon places wires, screws, and surgical implants through the muscles and bony structures under image guidance. These interventions require alignment of the pre- and intra-operative patient data, the intra-operative scanner, surgical instruments, and the patient. Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies.
State of the art approaches often support the surgeon by using external navigation systems or ill-conditioned image-based registration methods that both have certain drawbacks. Augmented reality (AR) has been introduced in the operating rooms in the last decade; however, in image-guided interventions, it has often only been considered as a visualization device improving traditional workflows. Consequently, the technology is gaining minimum maturity that it requires to redefine new procedures, user interfaces, and interactions.
This dissertation investigates the applications of AR, artificial intelligence, and robotics in interventional medicine. Our solutions were applied in a broad spectrum of problems for various tasks, namely improving imaging and acquisition, image computing and analytics for registration and image understanding, and enhancing the interventional visualization. The benefits of these approaches were also discovered in robot-assisted interventions.
We revealed how exemplary workflows are redefined via AR by taking full advantage of head-mounted displays when entirely co-registered with the imaging systems and the environment at all times. The proposed AR landscape is enabled by co-localizing the users and the imaging devices via the operating room environment and exploiting all involved frustums to move spatial information between different bodies. The system's awareness of the geometric and physical characteristics of X-ray imaging allows the exploration of different human-machine interfaces. We also leveraged the principles governing image formation and combined it with deep learning and RGBD sensing to fuse images and reconstruct interventional data.
We hope that our holistic approaches towards improving the interface of surgery and enhancing the usability of interventional imaging, not only augments the surgeon's capabilities but also augments the surgical team's experience in carrying out an effective intervention with reduced complications
Neural Radiance Fields: Past, Present, and Future
The various aspects like modeling and interpreting 3D environments and
surroundings have enticed humans to progress their research in 3D Computer
Vision, Computer Graphics, and Machine Learning. An attempt made by Mildenhall
et al in their paper about NeRFs (Neural Radiance Fields) led to a boom in
Computer Graphics, Robotics, Computer Vision, and the possible scope of
High-Resolution Low Storage Augmented Reality and Virtual Reality-based 3D
models have gained traction from res with more than 1000 preprints related to
NeRFs published. This paper serves as a bridge for people starting to study
these fields by building on the basics of Mathematics, Geometry, Computer
Vision, and Computer Graphics to the difficulties encountered in Implicit
Representations at the intersection of all these disciplines. This survey
provides the history of rendering, Implicit Learning, and NeRFs, the
progression of research on NeRFs, and the potential applications and
implications of NeRFs in today's world. In doing so, this survey categorizes
all the NeRF-related research in terms of the datasets used, objective
functions, applications solved, and evaluation criteria for these applications.Comment: 413 pages, 9 figures, 277 citation
Optical Methods in Sensing and Imaging for Medical and Biological Applications
The recent advances in optical sources and detectors have opened up new opportunities for sensing and imaging techniques which can be successfully used in biomedical and healthcare applications. This book, entitled âOptical Methods in Sensing and Imaging for Medical and Biological Applicationsâ, focuses on various aspects of the research and development related to these areas. The book will be a valuable source of information presenting the recent advances in optical methods and novel techniques, as well as their applications in the fields of biomedicine and healthcare, to anyone interested in this subject
Personalized Hip and Knee Joint Replacement
This open access book describes and illustrates the surgical techniques, implants, and technologies used for the purpose of personalized implantation of hip and knee components. This new and flourishing treatment philosophy offers important benefits over conventional systematic techniques, including component positioning appropriate to individual anatomy, improved surgical reproducibility and prosthetic performance, and a reduction in complications. The techniques described in the book aim to reproduce patientsâ native anatomy and physiological joint laxity, thereby improving the prosthetic hip/knee kinematics and functional outcomes in the quest of the forgotten joint. They include kinematically aligned total knee/total hip arthroplasty, partial knee replacement, and hip resurfacing. The relevance of available and emerging technological tools for these personalized approaches is also explained, with coverage of, for example, robotics, computer-assisted surgery, and augmented reality. Contributions from surgeons who are considered world leaders in diverse fields of this novel surgical philosophy make this open access book will invaluable to a wide readership, from trainees at all levels to consultants practicing lower limb surger
Actas de las XXXIV Jornadas de AutomĂĄtica
Postprint (published version