Edge-Enhancement DenseNet for X-ray Fluoroscopy Image Denoising in Cardiac Electrophysiology Procedures

PURPOSE: Reducing X‐ray dose increases safety in cardiac electrophysiology procedures but also increases image noise and artifacts which may affect the discernibility of devices and anatomical cues. Previous denoising methods based on convolutional neural networks (CNNs) have shown improvements in the quality of low‐dose X‐ray fluoroscopy images but may compromise clinically important details required by cardiologists. METHODS: In order to obtain denoised X‐ray fluoroscopy images whilst preserving details, we propose a novel deep‐learning‐based denoising framework, namely edge‐enhancement densenet (EEDN), in which an attention‐awareness edge‐enhancement module is designed to increase edge sharpness. In this framework, a CNN‐based denoiser is first used to generate an initial denoising result. Contours representing edge information are then extracted using an attention block and a group of interacted ultra‐dense blocks for edge feature representation. Finally, the initial denoising result and enhanced edges are combined to generate the final X‐ray image. The proposed denoising framework was tested on a total of 3262 clinical images taken from 100 low‐dose X‐ray sequences acquired from 20 patients. The performance was assessed by pairwise voting from five cardiologists as well as quantitative indicators. Furthermore, we evaluated our technique's effect on catheter detection using 416 images containing coronary sinus catheters in order to examine its influence as a pre‐processing tool. RESULTS: The average signal‐to‐noise ratio of X‐ray images denoised with EEDN was 24.5, which was 2.2 times higher than that of the original images. The accuracy of catheter detection from EEDN denoised sequences showed no significant difference compared with their original counterparts. Moreover, EEDN received the highest average votes in our clinician assessment when compared to our existing technique and the original images. CONCLUSION: The proposed deep learning‐based framework shows promising capability for denoising interventional X‐ray fluoroscopy images. The results from the catheter detection show that the network does not affect the results of such an algorithm when used as a pre‐processing step. The extensive qualitative and quantitative evaluations suggest that the network may be of benefit to reduce radiation dose when applied in real time in the catheter laboratory

Real-Time Quantum Noise Suppression In Very Low-Dose Fluoroscopy

Fluoroscopy provides real-time X-ray screening of patient's organs and of various radiopaque objects, which make it an invaluable tool for many interventional procedures. For this reason, the number of fluoroscopy screenings has experienced a consistent growth in the last decades. However, this trend has raised many concerns about the increase in X-ray exposure, as even low-dose procedures turned out to be not as safe as they were considered, thus demanding a rigorous monitoring of the X-ray dose delivered to the patients and to the exposed medical staff. In this context, the use of very low-dose protocols would be extremely beneficial. Nonetheless, this would result in very noisy images, which need to be suitably denoised in real-time to support interventional procedures. Simple smoothing filters tend to produce blurring effects that undermines the visibility of object boundaries, which is essential for the human eye to understand the imaged scene. Therefore, some denoising strategies embed noise statistics-based criteria to improve their denoising performances. This dissertation focuses on the Noise Variance Conditioned Average (NVCA) algorithm, which takes advantage of the a priori knowledge of quantum noise statistics to perform noise reduction while preserving the edges and has already outperformed many state-of-the-art methods in the denoising of images corrupted by quantum noise, while also being suitable for real-time hardware implementation. Different issues are addressed that currently limit the actual use of very low-dose protocols in clinical practice, e.g. the evaluation of actual performances of denoising algorithms in very low-dose conditions, the optimization of tuning parameters to obtain the best denoising performances, the design of an index to properly measure the quality of X-ray images, and the assessment of an a priori noise characterization approach to account for time-varying noise statistics due to changes of X-ray tube settings. An improved NVCA algorithm is also presented, along with its real-time hardware implementation on a Field Programmable Gate Array (FPGA). The novel algorithm provides more efficient noise reduction performances also for low-contrast moving objects, thus relaxing the trade-off between noise reduction and edge preservation, while providing a further reduction of hardware complexity, which allows for low usage of logic resources also on small FPGA platforms. The results presented in this dissertation provide the means for future studies aimed at embedding the NVCA algorithm in commercial fluoroscopic devices to accomplish real-time denoising of very low-dose X-ray images, which would foster their actual use in clinical practice

3D Imaging for Planning of Minimally Invasive Surgical Procedures

Novel minimally invasive surgeries are used for treating cardiovascular diseases and are performed under 2D fluoroscopic guidance with a C-arm system. 3D multidetector row computed tomography (MDCT) images are routinely used for preprocedural planning and postprocedural follow-up. For preprocedural planning, the ability to integrate the MDCT with fluoroscopic images for intraprocedural guidance is of clinical interest. Registration may be facilitated by rotating the C-arm to acquire 3D C-arm CT images. This dissertation describes the development of optimal scan and contrast parameters for C-arm CT in 6 swine. A 5-s ungated C-arm CT acquisition during rapid ventricular pacing with aortic root injection using minimal contrast (36 mL), producing high attenuation (1226), few artifacts (2.0), and measurements similar to those from MDCT (p\u3e0.05) was determined optimal. 3D MDCT and C-arm CT images were registered to overlay the aortic structures from MDCT onto fluoroscopic images for guidance in placing the prosthesis. This work also describes the development of a methodology to develop power equation (R2\u3e0.998) for estimating dose with C-arm CT based on applied tube voltage. Application in 10 patients yielded 5.48┬▒177 2.02 mGy indicating minimal radiation burden. For postprocedural follow-up, combinations of non-contrast, arterial, venous single energy CT (SECT) scans are used to monitor patients at multiple time intervals resulting in high cumulative radiation dose. Employing a single dual-energy CT (DECT) scan to replace two SECT scans can reduce dose. This work focuses on evaluating the feasibility of DECT imaging in the arterial phase. The replacement of non-contrast and arterial SECT acquisitions with one arterial DECT acquisition in 30 patients allowed generation of virtual non-contrast (VNC) images with 31 dose savings. Aortic luminal attenuation in VNC (32┬▒177 2 HU) was similar to true non-contrast images (35┬▒177 4 HU) indicating presence of unattenuated blood. To improve discrimination between c

Measurement of intervertebral cervical motion by means of dynamic X-ray image processing and data interpolation

Accurate measurement of intervertebral kinematics of the cervical spine can support the diagnosis of widespread diseases related to neck pain, such chronic whiplash dysfunction, arthritis, segmental degeneration. The natural inaccessibility of the spine, its complex anatomy and the small range of motion only permit concise measurement in-vivo. Low dose X-ray fluoroscopy allows time-continuous screening of cervical spine during patient’s spontaneous motion. To obtain accurate motion measurements, each vertebra was tracked by means of image processing along a sequence of radiographic images. To obtain a time-continuous representation of motion and to reduce noise in the experimental data, smoothing spline interpolation was used. Estimation of intervertebral motion for cervical segments was obtained by processing patient’s fluoroscopic sequence: intervertebral angle and displacement and the instantaneous centre of rotation were computed. The RMS value of fitting errors resulted about 0.2 degree for rotation and 0.2 mm for displacement

3D Imaging for Planning of Minimally Invasive Surgical Procedures

Novel minimally invasive surgeries are used for treating cardiovascular diseases and are performed under 2D fluoroscopic guidance with a C-arm system. 3D multidetector row computed tomography (MDCT) images are routinely used for preprocedural planning and postprocedural follow-up. For preprocedural planning, the ability to integrate the MDCT with fluoroscopic images for intraprocedural guidance is of clinical interest. Registration may be facilitated by rotating the C-arm to acquire 3D C-arm CT images. This dissertation describes the development of optimal scan and contrast parameters for C-arm CT in 6 swine. A 5-s ungated C-arm CT acquisition during rapid ventricular pacing with aortic root injection using minimal contrast (36 mL), producing high attenuation (1226), few artifacts (2.0), and measurements similar to those from MDCT (p\u3e0.05) was determined optimal. 3D MDCT and C-arm CT images were registered to overlay the aortic structures from MDCT onto fluoroscopic images for guidance in placing the prosthesis. This work also describes the development of a methodology to develop power equation (R2\u3e0.998) for estimating dose with C-arm CT based on applied tube voltage. Application in 10 patients yielded 5.48┬▒177 2.02 mGy indicating minimal radiation burden. For postprocedural follow-up, combinations of non-contrast, arterial, venous single energy CT (SECT) scans are used to monitor patients at multiple time intervals resulting in high cumulative radiation dose. Employing a single dual-energy CT (DECT) scan to replace two SECT scans can reduce dose. This work focuses on evaluating the feasibility of DECT imaging in the arterial phase. The replacement of non-contrast and arterial SECT acquisitions with one arterial DECT acquisition in 30 patients allowed generation of virtual non-contrast (VNC) images with 31 dose savings. Aortic luminal attenuation in VNC (32┬▒177 2 HU) was similar to true non-contrast images (35┬▒177 4 HU) indicating presence of unattenuated blood. To improve discrimination between c

Development and Implementation of Mathematical Modeling, Vibration and Acoustic Emission Technique to Correlate \u3cem\u3eIn Vivo\u3c/em\u3e Kinematics, Kinetics and Sound in Total Hip Arthroplasty with Different Bearing Surfaces

The evaluation of Total Hip Arthroplasty (THA) outcome is difficult and invasive methods are often applied. Fluoroscopy has been used as an in vivo diagnostic technique to determine separation which may lead to vibration propagation and audible interactions. The objective of this study was to develop a new, non-invasive technique of digitally capturing vibration and sound emissions at the hip joint interface and to correlate those with the hip kinematics derived from fluoroscopy. Additionally, an examination of the role of hip mechanics on walking performance in THA subjects of various bearings surfaces was performed. In vivo kinematics, kinetics, corresponding vibration and sound measurements of THA were analyzed post-operatively using video-fluoroscopy, mathematical modeling, sound sensors and accelerometers during gait on a treadmill. Twenty-seven subjects (31 hips) with a metal-on-metal, metal-on-polyethylene, ceramic-on-ceramic, ceramicon- polyethylene or metal-on-metal polyethylene-sandwich THA were analyzed. A data acquisition system was used to amplify the signal and filter out associated frequencies attributed to noise. The sound measurements were correlated to in vivo kinematics. A mathematical model of the human extremity was derived to determine in vivo bearing and soft-tissue forces. For all bearings a distinct correlation of a high frequency sound occurring at the time when the femoral head slides back into the acetabular component was observed. Subjects having a hard-on-hard bearing seemed to attenuate a squeaking and/or impacting sound, while those having polyethylene liner only revealed a knocking sound attributed to impact loading conditions. For the first time, audible effects can be derived in vivo and the examined correlation brings valuable insight into the hip joint performance in an inexpensive and non-invasive manner. This research may allow for a further correlation to be derived between sound and different types of failure mechanisms. Results from this study will give surgeons and engineers a better understanding of in vivo mechanics of the hip joint and this way improve the quality of life of THA patients. In addition, the developed technique builds the first milestone in the design and implementation of a cost effective, non-invasive diagnostic technique which has the potential to become a routine diagnosis of joint conditions

Measurement of intervertebral cervical motion by means of dynamic X-ray image processing and data interpolation

Accurate measurement of intervertebral kinematics of the cervical spine can support the diagnosis of widespread diseases related to neck pain, such as chronic whiplash dysfunction, arthritis, and segmental degeneration. The natural inaccessibility of the spine, its complex anatomy, and the small range of motion only permit concise measurement in vivo. Low dose X-ray fluoroscopy allows time-continuous screening of cervical spine during patient's spontaneous motion. To obtain accurate motion measurements, each vertebra was tracked by means of image processing along a sequence of radiographic images. To obtain a time-continuous representation of motion and to reduce noise in the experimental data, smoothing spline interpolation was used. Estimation of intervertebral motion for cervical segments was obtained by processing patient's fluoroscopic sequence; intervertebral angle and displacement and the instantaneous centre of rotation were computed. The RMS value of fitting errors resulted in about 0.2 degree for rotation and 0.2 mm for displacements

Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

Constrained Stochastic State Estimation of Deformable 1D Objects: Application to Single-view 3D Reconstruction of Catheters with Radio-opaque Markers

International audienceMinimally invasive fluoroscopy-based procedures are the gold standard for diagnosis and treatment of various pathologies of the cardiovascular system. This kind of procedures imply for the clinicians to infer the 3D shape of the device from 2D images, which is known to be an ill-posed 10 problem. In this paper we present a method to reconstruct the 3D shape of the interventional device, with the aim of improving the navigation. The method combines a physics-based simulation with non-linear Bayesian filter. Whereas the physics-based model provides a prediction of the shape of the device navigating within the blood vessels (taking into account non-linear interactions be-15 tween the catheter and the surrounding anatomy), an Unscented Kalman Filter is used to correct the navigation model using 2D image features as external observations. The proposed framework has been evaluated on both synthetic and real data, under different model parameterizations, filter parameters tuning and external observations data-sets. Comparing the reconstructed 3D shape with a known ground truth, for the synthetic data-set, we obtained average values for 3D Hausdorff Distance of $0.81 ± 0.53 mm$, for the 3D mean distance at the segment of $0.37 ± 0.17$ mm and an average 3D tip error of $0.24 ± 0.13 mm$. For the real data-set,we obtained an average 3D Hausdorff distance of $1.74 ± 0.77 mm$, a average 3D mean distance at the distal segment of 0.91 ± 0.14 mm, an average 3D error on the tip of $0.53 ± 0.09 mm$. These results show the ability of our method to retrieve the 3D shape of the device, under a variety of filter parameterizations and challenging conditions: uncertainties on model parameterization, ambiguous views and non-linear complex phenomena such as stick and slip motions

Signal, noise power spectrum, and detective quantum efficiency of indirectâ detection flatâ panel imagers for diagnostic radiology

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135120/1/mp8243.pd