Özgür Güler

Özgür Güler
eKare Inc.

PhD

About

76
Publications
11,708
Reads
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364
Citations
Citations since 2016
23 Research Items
260 Citations
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Introduction
I work in the area of computer assisted surgery (CAS) and robotics, computer vision and machine learning. I implement open-source tools to enable CAS research in the lab and to investigate accuracy in detail and show pitfalls/misbeliefs in literature. I provide tools to teach/simulate CAS in the class room. I helped integrating a robot to place screws in orthopedics. I study wound assessment by capturing the topology of wounds and perform measurements and classification of tissue.
Additional affiliations
January 2012 - present
Children's National Medical Center
Position
  • Researcher
March 2008 - December 2011
Medizinische Universität Innsbruck
Position
  • Research Assistant
March 2008 - December 2011
University of Innsbruck
Position
  • Research Assistant

Publications

Publications (76)
Preprint
Full-text available
With the rapid development and integration of artificial intelligence (AI) methods in next-generation networks (NextG), AI algorithms have provided significant advantages for NextG in terms of frequency spectrum usage, bandwidth, latency, and security. A key feature of NextG is the integration of AI, i.e., self-learning architecture based on self-s...
Preprint
p>Future wireless networks \textcolor{black}{(5G and beyond),} also known as Next Generation or NextG, are the vision of forthcoming cellular systems, connecting billions of devices and people together. In the last decades, cellular networks have been dramatically growth with advanced telecommunication technologies for high-speed data transmission,...
Preprint
Full-text available
Future wireless networks (5G and beyond) are the vision of forthcoming cellular systems, connecting billions of devices and people together. In the last decades, cellular networks have been dramatically growth with advanced telecommunication technologies for high-speed data transmission, high cell capacity, and low latency. The main goal of those t...
Article
Full-text available
The solar photovoltaics (PV) energy resources have become more important with their significant contribution to the current power grid among renewable energy resources. However, the integration of the solar PV causes reliability issues in the power grid due to its high dependence on the weather condition. The predictability and stability of forecas...
Preprint
Full-text available
The design of a security scheme for beamforming prediction is critical for next-generation wireless networks (5G, 6G, and beyond). However, there is no consensus about protecting the beamforming prediction using deep learning algorithms in these networks. This paper presents the security vulnerabilities in deep learning for beamforming prediction u...
Article
Full-text available
Future wireless networks (5G and beyond), also known as Next Generation or NextG, are the vision of forthcoming cellular systems, connecting billions of devices and people together. In the last decades, cellular networks have dramatically grown with advanced telecommunication technologies for high-speed data transmission, high cell capacity, and lo...
Preprint
Full-text available
The use of solar photovoltaics (PV) energy provides additional resources to the electric power grid. The downside of this integration is that the solar power supply is unreliable and highly dependent on the weather condition. The predictability and stability of forecasting are critical for the full utilization of solar power. This study reviews and...
Conference Paper
Full-text available
The use of solar photovoltaics (PV) energy provides additional resources to the electric power grid. The downside of this integration is that the solar power supply is unreliable and highly dependent on the weather condition. The predictability and stability of forecasting are critical for the full utilization of solar power. This study reviews and...
Conference Paper
Full-text available
This paper presents an open architecture testbed for smart cities, called OpenCity, which is hosted at Virginia Commonwealth University (VCU). The OpenCity platform consists of data collection and processing units, database management, distributed performance management algorithms, and real-time data visualization. This smart city testbed aims to s...
Article
Full-text available
Artificial Intelligence (AI) has been among the most emerging research and industrial application fields, especially in the healthcare domain, but operated as a black-box model with a limited understanding of its inner working over the past decades. AI algorithms are, in large part, built on weights calculated as a result of large matrix multiplica...
Article
Full-text available
Abstract In part due to its ability to mimic any data distribution, Generative Adversarial Network (GAN) algorithms have been successfully applied to many applications, such as data augmentation, text‐to‐image translation, image‐to‐image translation, and image inpainting. Learning from data without crafting loss functions for each application provi...
Article
Full-text available
Abstract Generative adversarial network (GAN) applications on medical image synthesis have the potential to assist caregivers in deciding a proper chronic wound treatment plan by understanding the border segmentation and the wound tissue classification visually. This study proposes a hybrid wound border segmentation and tissue classification method...
Article
Full-text available
In recent years, the use of the Internet of Things (IoT) has increased exponentially, and cybersecurity concerns have increased along with it. On the cutting edge of cybersecurity is Artificial Intelligence (AI), which is used for the development of complex algorithms to protect networks and systems, including IoT systems. However, cyber-attackers...
Preprint
Full-text available
Artificial Intelligence (AI) has seen increased application and widespread adoption over the past decade despite, at times, offering a limited understanding of its inner working. AI algorithms are, in large part, built on weights, and these weights are calculated as a result of large matrix multiplications. Computationally intensive processes are t...
Article
Full-text available
Object detection and segmentation algorithms evolved significantly in the last decade. Simultaneous object detection and segmentation paved the way for real-time applications such as autonomous driving. Detection and segmentation of (partially) flooded roadways are essential inputs for vehicle routing and traffic management systems. This paper prop...
Article
Full-text available
Over the last two decades, Artificial Intelligence (AI) approaches have been applied to various applications of the smart grid, such as demand response, predictive maintenance, and load forecasting. However, AI is still considered to be a "black-box" due to its lack of explainability and transparency, especially for something like solar photovoltai...
Article
Full-text available
Purpose For orthopedic procedures, surgeons utilize intra-operative medical images such as fluoroscopy to plan screw placement and accurately position the guide wire with the intended trajectory. The number of fluoroscopic images needed depends on the complexity of the case and skill of the surgeon. Since more fluoroscopic images lead to more expos...
Conference Paper
Full-text available
Slipped Capital Femoral Epiphysis (SCFE) is a common pathologic hip condition in adolescents. In the standard treatment, a surgeon relies on multiple intra-operative fluoroscopic X-ray images to plan the screw placement and to guide a drill along the intended trajectory. More complex cases could require more images, and thereby, higher radiation do...
Conference Paper
Full-text available
Purpose Slipped Capital Femoral Epiphysis (SCFE) is a common hip displacement in adolescents, usually brought about during a growth spurt, that results in slippage of the posterior and inferior femoral epiphysis [1] . Symptoms of SCFE include gross or localized pain and decreased range of motion, particularly inward hip rotation. It is usually cons...
Conference Paper
Full-text available
In general, vocational education is crucial for a successful future career. We studied the impact of different teaching strategies and techniques on the learn-ing success for students in computer-assisted surgery. Frontal teaching, practical learning, and a mixture of both are investigated to find the most effective way. The success of learning is...
Article
Purpose: Registration is one of the key technical components in an image-guided navigation system. A large number of 2D/3D registration algorithms have been previously proposed, but have not been able to transition into clinical practice. The authors identify the primary reason for the lack of adoption with the prerequisite for a sufficiently accu...
Article
Full-text available
Background and Objectives During navigated procedures a tracked pointing device is used to define target structures in the patient to visualize its position in a registered radiologic data set. When working with endoscopes in minimal invasive procedures, the target region is often difficult to reach and changing instruments is disturbing in a chall...
Conference Paper
Full-text available
All 2D/3D anatomy based rigid registration algorithms are iterative, requiring an initial estimate of the 3D data pose. Current initialization methods have limited applicability in the operating room setting, due to the constraints imposed by this environment or due to insufficient accuracy. In this work we use the Microsoft Kinect device to allow...
Article
Full-text available
Purpose: The benefit of computer-assisted navigation depends on the registration process, at which patient features are correlated to some preoperative imagery. The operator-induced uncertainty in localizing patient features-the user localization error (ULE)-is unknown and most likely dominating the application accuracy. This initial feasibility s...
Chapter
We describe a technique for intraoperative initialization of 2D/3D registration. The technique uses a tracked tool that is already available in the operating room, as part of an image-guided navigation system, to establish the transformation between the preoperative volume and the intraoperative patient. Initialization is performed in two phases: v...
Article
Full-text available
Teaching the key technical aspects of image-guided interventions using a hands-on approach is a challenging task. This is primarily due to the high cost and lack of accessibility to imaging and tracking systems. We provide a software and data infrastructure which addresses both challenges. Our infrastructure allows students, patients, and clinician...
Article
The Image-Guided Surgery Toolkit (IGSTK) provides tracker interfaces for various tracking devices. The tracker component of IGSTK was extended with three new tracking interfaces: CamBar B2, EasyTrack 500, and Active Polaris. Using an IGSTK application we evaluated the precision of each of the tracking systems. Based on our evaluation we conclude th...
Article
Full-text available
Computer assisted navigation systems that combine real-time endoscopy images with pre-operative volumetric data sets aim at improving the physician's understanding of the underlying anatomical structures. To achieve accurate and safe guidance these systems are required to provide a consistent representation of the physical world. This implies that...
Article
Full-text available
The purpose of this study is to evaluate apparent diffusion coefficient (ADC) maps to distinguish anti-vascular and anti-tumor effects in the course of anti-angiogenic treatment of recurrent high-grade gliomas (rHGG) as compared to standard magnetic resonance imaging (MRI). This retrospective study analyzed ADC maps from diffusion-weighted MRI in 1...
Article
Full-text available
Background The main source of error in 3D navigation is the patient-to-image registration process. Anatomical landmarks or adhesive markers perform sub-optimally. Bone-anchored invasive markers significantly change the clinical workflow of navigated ENT surgery, are invasive and cause patient discomfort. In order to minimize registration errors and...
Article
Full-text available
The main source of error in 3D navigation is the patient-to-image registration process. Anatomical landmarks or adhesive markers perform sub-optimally. Bone-anchored invasive markers significantly change the clinical workflow of navigated ENT surgery, are invasive and cause patient discomfort. In order to minimize registration errors and to further...
Chapter
Full-text available
In the last decades the Internet has changed traditional understanding of retrieving and distributing information. Knowledge and specialists are permanently reachable regardless of geographical distances. Special software development strategies were created to increase and exploit the power of distributed development and testing. This access to dis...
Article
Full-text available
In a detailed laboratory investigation we performed a series of experiments in order to assess the validity of the widely used TRE concept to predict the application accuracy. On base of 1mm CT scan a plastic skull, a cadaver head and a volunteer were registered to an in house navigation system. We stored the position data of an optical camera (NDI...
Chapter
Full-text available
Endoscopic and video-endoscopic procedures in ENT and neurosurgical interventions are ideally apt for navigation. 3D-Navigation with endoscopy satisfies the surgical demand of precise information regarding localization of instruments in the patient’s anatomy. We provide a solution augmenting surgical performance and acceptance: a 3D-navigated (vide...
Conference Paper
Full-text available
Details of commercially available navigation systems are not open to the public. With the development of our open source 3D-navigation system, open4Dnav, new possibilities in evaluating and testing new components and parameters can be achieved. To determine the application accuracy of open4Dnav a large number of measurements were evaluated. The reg...