C-arm X-ray Imaging Research Articles

Take a shot! Natural language control of intelligent robotic X-ray systems in surgery.

The expanding capabilities of surgical systems bring with them increasing complexity in the interfaces that humans use to control them. Robotic C-arm X-ray imaging systems, for instance, often require manipulation of independent axes via joysticks, while higher-level control options hide inside device-specific menus. The complexity of these interfaces hinder "ready-to-hand" use of high-level functions. Natural language offers a flexible, familiar interface for surgeons to express their desired outcome rather than remembering the steps necessary to achieve it, enabling direct access to task-aware, patient-specific C-arm functionality. We present an English language voice interface for controlling a robotic X-ray imaging system with task-aware functions for pelvic trauma surgery. Our fully integrated system uses a large language model (LLM) to convert natural spoken commands into machine-readable instructions, enabling low-level commands like "Tilt back a bit," to increase the angular tilt or patient-specific directions like, "Go to the obturator oblique view of the right ramus," based on automated image analysis. We evaluate our system with 212 prompts provided by an attending physician, in which the system performed satisfactory actions 97% of the time. To test the fully integrated system, we conduct a real-time study in which an attending physician placed orthopedic hardware along desired trajectories through an anthropomorphic phantom, interacting solely with an X-ray system via voice. Voice interfaces offer a convenient, flexible way for surgeons to manipulate C-arms based on desired outcomes rather than device-specific processes. As LLMs grow increasingly capable, so too will their applications in supporting higher-level interactions with surgical assistance systems.

VDVM: An automatic vertebrae detection and vertebral segment matching framework for C-arm X-ray image identification.

C-arm fluoroscopy, as an effective diagnosis and treatment method for spine surgery, can help doctors perform surgery procedures more precisely. In clinical surgery, the surgeon often determines the specific surgical location by comparing C-arm X-ray images with digital radiography (DR) images. However, this heavily relies on the doctor's experience. In this study, we design a framework for automatic vertebrae detection as well as vertebral segment matching (VDVM) for the identification of vertebrae in C-arm X-ray images. The proposed VDVM framework is mainly divided into two parts: vertebra detection and vertebra matching. In the first part, a data preprocessing method is used to improve the image quality of C-arm X-ray images and DR images. The YOLOv3 model is then used to detect the vertebrae, and the vertebral regions are extracted based on their position. In the second part, the Mobile-Unet model is first used to segment the vertebrae contour of the C-arm X-ray image and DR image based on vertebral regions respectively. The inclination angle of the contour is then calculated using the minimum bounding rectangle and corrected accordingly. Finally, a multi-vertebra strategy is applied to measure the visual information fidelity for the vertebral region, and the vertebrae are matched based on the measured results. We use 382 C-arm X-ray images and 203 full length X-ray images to train the vertebra detection model, and achieve a mAP of 0.87 in the test dataset of 31 C-arm X-ray images and 0.96 in the test dataset of 31 lumbar DR images. Finally, we achieve a vertebral segment matching accuracy of 0.733 on 31 C-arm X-ray images. A VDVM framework is proposed, which performs well for the detection of vertebrae and achieves good results in vertebral segment matching.

Toward an End-to-End Calibration for Mobile C-Arm in Combination with a Depth Sensor for Surgical Augmented Reality Applications.

C-arm X-ray imaging is commonly applied in operating rooms for guiding orthopedic surgeries. Augmented Reality (AR) with C-arm X-ray images during surgery is an efficient way to facilitate procedures for surgeons. However, the accurate calibration process for surgical AR based on C-arm is essential and still challenging due to the limitations of C-arm imaging systems, such as instability of C-arm calibration parameters and the narrow field of view. We extend existing methods using a depth camera and propose a new calibration procedure consisting of calibration of the C-arm imaging system, and 3D/2D calibration of an RGB-D camera and C-arm system with a new method to achieve reliable data and promising accuracy and, at the same time, consistent with standard surgical protocols. For the calibration procedure, we apply bundle adjustment equations with a 3D designed Lego multi-modal phantom, in contrast to the previous methods in which planar calibration phantoms were applied. By using our method, the visualization of the X-ray image upon the 3D data was done, and the achieved mean overlay error was 1.03 mm. The evaluations showed that the proposed calibration procedure provided promising accuracy for AR surgeries and it improved the flexibility and robustness of existing C-arm calibration methods for surgical augmented reality (using C-arm and RGB-D sensor). Moreover, the results showed the efficiency of our method to compensate for the effects of the C-arm movement on calibration parameters. It was shown that the obtained overlay error was improved for the non-zero rotation movement of C-arm by using a virtual detector.

C-ARM POSE ESTIMATION AND NAVIGATION IN SURGERIES FOR AUGMENTED REALITY APPLICATION

Abstract. C-arm X-ray imaging systems are widely applied in surgeries. Overlaying X-ray with optical images during the surgery has been shown to be an efficient approach. Moreover, overlaying needed data from different modalities in an augmented reality (AR) manner can improve the accuracy of surgical procedures, decrease the variability of surgical outcomes, reduce trauma to the critical structures, increase the reproducibility of surgeons’ performance, and reduce radiation exposure. C-Arm geometric calibration and recovering the C-arm pose are essential for surgical navigation and AR applications in operating rooms. Therefore, in this paper, existing researches for calibration and pose estimation of C-arm devices in surgical AR applications are evaluated from photogrammetric point of view. Then, a proposed marker-based method for C-arm pose estimation is introduced. For this purpose, a marker is designed to facilitate tracking and pose estimation in mixed reality based on golden section principle, and perspective invariants such as cross-ratios, collinearity, and intersection. Moreover, a procedure is also proposed for fast determination of these fiducial markers. The experiments show benefits of such a structure which has a limited occlusion with consistency to different conditions such as narrow field of view and at the same time, even in images with high projectivity. It also results that the distortion correction step is important and the effect of distortion of X-ray images can cause inconsistency in the perspective invariants.

Using C-Arm X-ray images from marker insertion to confirm the gold fiducial marker identification in an MRI-only prostate radiotherapy workflow.

Prostate cancer radiotherapy workflows, solely based on magnetic resonance imaging (MRI), are now in clinical use. In these workflows, intraprostatic gold fiducial markers (GFM) show similar signal behavior as calcifications and bleeding in T2‐weighted MRI‐images. Accurate GFM identification in MRI‐only radiotherapy workflows is therefore a major challenge. C‐arm X‐ray images (CkV‐images), acquired at GFM implantation, could provide GFM position information and be used to confirm correct identification in T2‐weighted MRI‐images. This would require negligible GFM migration between implantation and MRI‐imaging. Marker migration was therefore investigated. The aim of this study was to show the feasibility of using CkV‐images to confirm GFM identification in an MRI‐only prostate radiotherapy workflow. An anterior‐posterior digitally reconstructed radiograph (DRR)‐image and a mirrored posterior‐anterior CkV‐image were acquired two weeks apart for 16 patients in an MRI‐only radiotherapy workflow. The DRR‐image originated from synthetic CT‐images (created from MRI‐images). A common image geometry was defined between the DRR‐ and CkV‐image for each patient. A rigid registration between the GFM center of mass (CoM) coordinates was performed and the distance between each of the GFM in the DRR‐ and registered CkV‐image was calculated. The same methodology was used to assess GFM migration for 31 patients in a CT‐based radiotherapy workflow. The distance calculated was considered a measure of GFM migration. A statistical test was performed to assess any difference between the cohorts. The mean absolute distance difference for the GFM CoM between the DRR‐ and CkV‐image in the MRI‐only cohort was 1.7 ± 1.4 mm. The mean GFM migration was 1.2 ± 0.7 mm. No significant difference between the measured total distances of the two cohorts could be detected (P = 0.37). This demonstrated that, a C‐Arm X‐ray image acquired from the GFM implantation procedure could be used to confirm GFM identification from MRI‐images. GFM migration was present but did not constitute a problem.

P139] Indication of accurate gold fiducial marker identification in a prostate MRI only radiotherapy workflow using C-arm X-ray imaging

Purpose Prostate cancer radiotherapy workflows solely based on magnetic resonance imaging (MRI), are now being clinically used. Intra-prostatic gold fiducial markers (GFM), appear as signal voids in MRI-images while calcifications and bleedings show similar signal behavior. Achieving accurate identification of GFM in an MRI-based workflow thereby constitute a major challenge. Several identification methods have been presented but none has reached an accuracy of 100%. C-arm X-ray images (CkV-images), acquired at GFM implantation, could provide GFM position information and be used to indicate correct identification. This would require negligible GFM migration. The aim of this study was to: 1) study the GFM migration 2) show the feasibility of using CkV-images as an indicator of accurate GFM identification. Methods Frontal digitally reconstructed radiographs (DRR)- and CkV-images were acquired two weeks apart for 31 patients in a CT-based radiotherapy workflow and for 16 patients in an MRI-based radiotherapy workflow. A common image geometry was defined between the DRR- and CkV-image for each patient. For each image, a point cloud was defined from the GFM center of mass coordinates. A rigid registration between the point clouds was performed and the distance between each of the GFM in the DRR- and registered CkV-image was calculated. The distance calculated in the CT-based patient cohort was considered a measure of GFM migration. A statistical test was performed to assess any difference between the cohorts. Results The mean GFM migration assessed in the CT-based patient cohort was 1.2 ± 0.7 mm. The mean absolute distance difference for the GFM center of mass in the MRI-based cohort was 1.7 ± 1.4 mm. No significant difference between the measured total distances of the two patient cohorts could be detected (p-value = 0.37). Conclusions A C-Arm X-ray image acquired from the GFM implantation procedure could be used as an indicator of accurate GFM identification. GFM migration was present but did not constitute a problem for the proposed method.

Plan in 2-D, execute in 3-D: an augmented reality solution for cup placement in total hip arthroplasty.

Reproducibly achieving proper implant alignment is a critical step in total hip arthroplasty procedures that has been shown to substantially affect patient outcome. In current practice, correct alignment of the acetabular cup is verified in C-arm x-ray images that are acquired in an anterior-posterior (AP) view. Favorable surgical outcome is, therefore, heavily dependent on the surgeon's experience in understanding the 3-D orientation of a hemispheric implant from 2-D AP projection images. This work proposes an easy to use intraoperative component planning system based on two C-arm x-ray images that are combined with 3-D augmented reality (AR) visualization that simplifies impactor and cup placement according to the planning by providing a real-time RGBD data overlay. We evaluate the feasibility of our system in a user study comprising four orthopedic surgeons at the Johns Hopkins Hospital and report errors in translation, anteversion, and abduction as low as 1.98mm, 1.10deg, and 0.53deg, respectively. The promising performance of this AR solution shows that deploying this system could eliminate the need for excessive radiation, simplify the intervention, and enable reproducibly accurate placement of acetabular implants.

Can real-time RGBD enhance intraoperative Cone-Beam CT?

Cone-Beam Computed Tomography (CBCT) is an important 3D imaging technology for orthopedic, trauma, radiotherapy guidance, angiography, and dental applications. The major limitation of CBCT is the poor image quality due to scattered radiation, truncation, and patient movement. In this work, we propose to incorporate information from a co-registered Red-Green-Blue-Depth (RGBD) sensor attached near the detector plane of the C-arm to improve the reconstruction quality, as well as correcting for undesired rigid patient movement. Calibration of the RGBD and C-arm imaging devices is performed in two steps: (i) calibration of the RGBD sensor and the X-ray source using a multimodal checkerboard pattern, and (ii) calibration of the RGBD surface reconstruction to the CBCT volume. The patient surface is acquired during the CBCT scan and then used as prior information for the reconstruction using Maximum-Likelihood Expectation-Maximization. An RGBD-based simultaneous localization and mapping method is utilized to estimate the rigid patient movement during scanning. Performance is quantified and demonstrated using artificial data and bone phantoms with and without metal implants. Finally, we present movement-corrected CBCT reconstructions based on RGBD data on an animal specimen, where the average voxel intensity difference reduces from 0.157 without correction to 0.022 with correction. This work investigated the advantages of a C-arm X-ray imaging system used with an attached RGBD sensor. The experiments show the benefits of the opto/X-ray imaging system in: (i) improving the quality of reconstruction by incorporating the surface information of the patient, reducing the streak artifacts as well as the number of required projections, and (ii) recovering the scanning trajectory for the reconstruction in the presence of undesired patient rigid movement.

Information Processing in Computer-Assisted Interventions: 4th International Conference, 2013.

Information Processing in Computer-Assisted Interventions: 4th International Conference, 2013.

Using C-Arm X-Ray Imaging to Guide Local Reporter Probe Delivery for Tracking Stem Cell Engraftment

Poor cell survival and difficulties with visualization of cell delivery are major problems with current cell transplantation methods. To protect cells from early destruction, microencapsulation methods have been developed. The addition of a contrast agent to the microcapsule also could enable tracking by MR, ultrasound, and X-ray imaging. However, determining the cell viability within the microcapsule still remains an issue. Reporter gene imaging provides a way to determine cell viability, but delivery of the reporter probe by systemic injection may be hindered in ischemic diseases.In the present study, mesenchymal stem cells (MSCs) were transfected with triple fusion reporter gene containing red fluorescent protein, truncated thymidine kinase (SPECT/PET reporter) and firefly luciferase (bioluminescence reporter). Transfected cells were microencapsulated in either unlabeled or perfluorooctylbromide (PFOB) impregnated alginate. The addition of PFOB provided radiopacity to enable visualization of the microcapsules by X-ray imaging. Before intramuscular transplantation in rabbit thigh muscle, the microcapsules were incubated with D-luciferin, and bioluminescence imaging (BLI) was performed immediately. Twenty-four and forty-eight hours post transplantation, c-arm CT was used to target the luciferin to the X-ray-visible microcapsules for BLI cell viability assessment, rather than systemic reporter probe injections. Not only was the bioluminescent signal emission from the PFOB-encapsulated MSCs confirmed as compared to non-encapsulated, naked MSCs, but over 90% of injection sites of PFOB-encapsulated MSCs were visible on c-arm CT. The latter aided in successful targeting of the reporter probe to injection sites using conventional X-ray imaging to determine cell viability at 1-2 days post transplantation. Blind luciferin injections to the approximate location of unlabeled microcapsules resulted in successful BLI signal detection in only 18% of injections. In conclusion, reporter gene probes can be more precisely targeted using c-arm CT for in vivo transplant viability assessment, thereby avoiding large and costly systemic injections of a reporter probe.

Closed-Form Inverse Kinematics for Interventional C-Arm X-Ray Imaging With Six Degrees of Freedom: Modeling and Application

For trauma and orthopedic surgery, maneuvering a mobile C-arm fluoroscope into a desired position to acquire an X-ray is a routine surgical task. The precision and ease of use of the C-arm becomes even more important for advanced interventional imaging techniques such as parallax-free X-ray image stitching. Today's standard mobile C-arms have been modeled with only five degrees of freedom (DOF), which definitely restricts their motions in 3-D Cartesian space. In this paper, we present a method to model both the mobile C-arm and patient's table as an integrated kinematic chain having six DOF without constraining table position. The closed-form solutions for the inverse kinematics problem are derived in order to obtain the required values for all C-arm joint and table movements to position the fluoroscope at a desired pose. The modeling method and the closed-form solutions can be applied to general isocentric or nonisocentric mobile C-arms. By achieving this we develop an efficient and intuitive inverse kinematics-based method for parallax-free panoramic X-ray imaging. In addition, we implement a 6-DOF C-arm system from a low-cost mobile fluoroscope to optimally acquire X-ray images based solely on the computation of the required movement for each joint by solving the inverse kinematics on a continuous basis. Through simulation experimentation, we demonstrate that the 6-DOF C-arm model has a larger working space than the 5-DOF model. C-arm repositioning experiments show the practicality and accuracy of our 6-DOF C-arm system. We also evaluate the novel parallax-free X-ray stitching method on phantom and dry bones. Using five trials, results show that parallax-free panoramas generated by our method are of high visual quality and within clinical tolerances for accurate evaluation of long bone geometry (i.e., image and metric measurement errors are less than 1% compared to ground-truth).

Outcome of bilateral ureteroscopic retrieval of stones in a single session

Aim:Evaluation of bilateral ureteroscopic retrieval of stones as a single-stage procedure in terms of clearance of the stones, complications of the procedure and duration of hospital stay. A successful outcome was considered when both ureters were free of stones without any major complications.Materials and Methods:A total of 60 patients with bilateral ureteric stones were treated ureteroscopically from March 2006 to September 2009 in the department of Surgery (Urology unit). Majority of the patients were in their third and fourth decade of life with 38 males and 22 females. A single session bilateral ureteroscopic retrieval of stones was done using a 7.8 Fr semirigid ureteroscope. A 0.038-inch guide wire was used and advanced under direct vision, and monitored by C-arm X-ray image intensifier. Balloon dilatation of the intramural ureters was required in 82 renal units. The stones were either extracted directly or disintegrated into small pieces by lithotripsy (pneumatic) before extraction. Ureteric stenting was required in 39 patients. Patients were followed for a period of 3-12 months.Results:A total of 60 patients (120 renal units) with bilateral ureteric stones were treated ureteroscopically. The stone size in the treated patients was in the range 6-20 mm. The stones were radio-opaque in 47 patients and radiolucent in 13 patients. Single stone was present in all except two patients. Operative time ranged between 40 and 120 minutes. Stones were completely removed in 51 (85%) patients following single-session procedure of which 39 (76.4%) were stonefree intraoperatively and another 12 (23.5%) were cleared of the stones in 4 weeks follow-up. Six patients were stonefree unilaterally. Failed procedures were managed with repeated ureteroscopy, DJ stenting and ESWL or open ureterolithotomy. Intraoperatively false passage or minor ureteric perforations were seen in six patients. Postoperative complications included abdominal pain in 10, persistent fever in 4 and hematuria in 2 patients. No long-term complications were observed. Most of the patients were discharged in 2 days.Conclusion:Bilateral same-session ureteroscopy is a safe and effective procedure in the management of bilateral ureteral stones. The results are comparable to unilateral or staged bilateral procedures.

Nano iron oxide–hydroxyapatite composite ceramics with enhanced radiopacity

Hydroxyapatite has been widely used for a variety of bone filling and augmentation applications. But the poorly resolved X-ray image of certain hydroxyapatite (HA) based implants such as porous blocks and self setting HA cements is a radiological problem to surgeons for monitoring of the implant and early diagnosis complications. In the present work the practical difficulty related to the reduced X-ray opacity was overcome by exploiting the contrast enhancement property of iron oxide nano particles. Sintered nano iron oxide-HA composite ceramics were prepared from powders produced through a co-precipitation route. The phase purity and bioactivity of the composites were analyzed as a function of percentage iron oxide in the composite. The X-ray attenuation of dense and porous composites was compared with pure HA using a C-arm X-ray imaging system and micro computed tomography. In all the prepared composites, HA retains its phase identity and high X-ray opacity as obtained for a composition containing 40 wt% iron oxide. The increased cell viability and cell adhesion nature depicted by the prepared composite offers considerable interest for the material in bone tissue engineering applications.

Targeted 2D/3D registration using ray normalization and a hybrid optimizer

X-ray images are often used to guide minimally invasive procedures in interventional radiology. The use of a preoperatively obtained 3D volume can enhance the visualization needed for guiding catheters and other surgical devices. However, for intraoperative usefulness, the 3D dataset needs to be registered to the 2D x-ray images of the patient. We investigated the effect of targeting subvolumes of interest in the 3D datasets and registering the projections with C-arm x-ray images. We developed an intensity-based 2D/3D rigid-body registration using a Monte Carlo-based hybrid algorithm as the optimizer, using a single view for registration. Pattern intensity (PI) and mutual information (MI) were two metrics tested. We used normalization of the rays to address the problems due to truncation in 3D necessary for targeting. We tested the algorithm on a C-arm x-ray image of a pig's head and a 3D dataset reconstructed from multiple views of the C-arm. PI and MI were comparable in performance. For two subvolumes starting with a set of initial poses from +/-15 mm in x, from +/-3 mm (random), in y and z and +/-4 deg in the three angles, the robustness was 94% for PI and 91% for MI, with accuracy of 2.4 mm (PI) and 2.6 mm (MI), using the hybrid algorithm. The hybrid optimizer, when compared with a standard Powell's direction set method, increased the robustness from 59% (Powell) to 94% (hybrid). Another set of 50 random initial conditions from [+/-20] mm in x,y,z and [+/-10] deg in the three angles, yielded robustness of 84% (hybrid) versus 38% (Powell) using PI as metric, with accuracies 2.1 mm (hybrid) versus 2.0 mm (Powell).

Sensor, Signal and Image Informatics

The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.