Tomography Image Acquisition Research Articles

Image reconstruction method of gamma emission tomography based on prior-aware information and machine learning for partial-defect detection of PWR-type spent nuclear fuel

Spent nuclear fuel (SNF) requires accurate and effective supervision to prevent radiation release to the public and the environment. Gamma emission tomography (GET) has been used to inspect partial-defects at the pin-by-pin level through the acquisition of tomographic images. However, due to the high density of nuclear fuel rods, GET shows relatively low accuracy for the central region. This study proposes an image reconstruction method for the internal fuels based on Monte Carlo simulation and machine learning algorithm. The gammas from the SNF were measured with the GET device and the sinograms were reconstructed with Maximum-Likelihood Expectation-Maximization (MLEM) with prior-aware information of SNF, and image quality was improved with the machine learning technique. Our results show that the MLEM with prior-aware information could dramatically improve the image quality and the denoising technique with the machine learning could clearly correct the over-and under-estimation. Based on the results of quantitative validation of the proposed reconstruction method, the pattern classification accuracy was calculated to be about 100 %. These techniques enabled the image acquisition of the central fuel rod and increased accuracy in partial defect detection. For further study, the performance of the proposed reconstruction method will be evaluated based on the experiment data.

CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the plane. Leveraging cell continuity in consecutive -stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process. The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.

Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence

The primary objective of the present study was to identify a subset of radiomic features extracted from primary tumor imaged by computed tomography of early-stage non-small cell lung cancer patients, which remain unaffected by variations in segmentation quality and in computed tomography image acquisition protocol. The robustness of these features to segmentation variations was assessed by analyzing the correlation of feature values extracted from lesion volumes delineated by two annotators. The robustness to variations in acquisition protocol was evaluated by examining the correlation of features extracted from high-dose and low-dose computed tomography scans, both of which were acquired for each patient as part of the stereotactic body radiotherapy planning process. Among 106 radiomic features considered, 21 were identified as robust. An analysis including univariate and multivariate assessments was subsequently conducted to estimate the predictive performance of these robust features on the outcome of early-stage non-small cell lung cancer patients treated with stereotactic body radiation therapy. The univariate predictive analysis revealed that robust features demonstrated superior predictive potential compared to non-robust features. The multivariate analysis indicated that linear regression models built with robust features displayed greater generalization capabilities by outperforming other models in predicting the outcomes of an external validation dataset.

A Clinic-Radiomics Model for Predicting the Incidence of Persistent Organ Failure in Patients with Acute Necrotizing Pancreatitis.

Persistent organ failure (POF) is the leading cause of death in patients with acute necrotizing pancreatitis (ANP). Although several risk factors have been identified, there remains a lack of efficient instruments to accurately predict the incidence of POF in ANP. Retrospectively, the clinical and imaging data of 178 patients with ANP were collected from our database, and the patients were divided into training (n = 125) and validation (n = 53) cohorts. Through computed tomography image acquisition, the volume of interest segmentation, and feature extraction and selection, a pure radiomics model in terms of POF prediction was established. Then, a clinic-radiomics model integrating the pure radiomics model and clinical risk factors was constructed. Both primary and secondary endpoints were compared between the high- and low-risk groups stratified by the clinic-radiomics model. According to the 547 selected radiomics features, four models were derived from features. A clinic-radiomics model in the training and validation sets showed better predictive performance than pure radiomics and clinical models. The clinic-radiomics model was evaluated by the ratios of intervention and mechanical ventilation, intensive care unit (ICU) stays, and hospital stays. The results showed that the high-risk group had significantly higher intervention rates, ICU stays, and hospital stays than the low-risk group, with the confidence interval of 90% (p < 0.1 for all). This clinic-radiomics model is a useful instrument for clinicians to evaluate the incidence of POF, facilitating patients' and their families' understanding of the ANP prognosis.

Cone-beam computed tomography (CBCT) dose optimization technique and image quality assessment scoring.

Linear accelerator (LINAC) embedded with kV source-imager system is capable to do image-guided radiotherapy. The only disadvantage of cone-beam computed tomography image acquisition during treatment is the extra radiation dose to the patient. The aim of this study is to optimize the CBCT imaging doses likely to be received by the patient undergoing radiotherapy without affecting image quality. The imaging dose to the patient was estimated on CTDI phantoms. The effect of additional filters of different materials (copper, brass, aluminum of thickness 0.1 mm each) was evaluated to find the optimized dose imaging technique. For the pelvis, a single imaging protocol available on the machine was used, whereas for the head and neck region, two protocols, high-quality head and standard-dose head were used. The image quality was assessed on CATPHAN-504 phantom using Owl CATPHAN® QA online tool. A new term "Image Assessment score" (IAS) was introduced to evaluate the image quality. In the pelvis protocol, CBCT imaging doses with an additional 0.1-mm brass, copper, and aluminum filter were measured to be reduced by 7.1%, 4.7%, and 2.5%, respectively, whereas for high-quality head protocol, the dose reduction was 25.4% (with brass filter), 22% (with copper filter), and 3.1% (with aluminum filter). For the standard-dose head protocol, doses were reduced by 7.5%, 2.8%, and 2.1% with additional 0.1-mm brass copper and aluminum filters, respectively. Acceptable image quality was observed with all the filters. Although the reconstructed images were found somewhat noisier, they did not affect the purpose of imaging, that is, treatment position verification. It was observed that these extra filters further reduce the imaging dose without much affecting the image quality.

Three-Dimensional Printing of the Patellofemoral Joints of Patellar Instability Patients

Three-dimensional (3D) modeling and printing comprise an important tool for orthopaedic surgeons. One area in which 3D modeling has the potential to dramatically improve our understanding of biomechanical kinematics is pathologies of the patellofemoral joint, in particular trochlear dysplasia. We describe a method for creating 3D printed models of the patellofemoral joint, including computed tomography image acquisition, image segmentation, model creation, and 3D printing. The models created can help surgeons understand and plan surgery for recurrent patellar dislocations.

Tomographic image reconstruction techniques for accurate spent fuel assembly verification

Non-proliferation and the security of nuclear materials are essential. The international atomic energy agency (IAEA) considers a tomographic image acquisition technique of spent fuel assemblies a promising technique to accurately verify the rod-by-rod spent fuel conditions stored in a water pool. Researchers at Yonsei University in Korea developed the bismuth germanate (BGO) scintillator-based Yonsei Single-photon Emission Computed Tomography (YSECT). Previous research validated the YSECT system experimentally to quickly evaluate the radioactivity distribution of test fuel rods in the Korea Institute of Nuclear Nonproliferation and Control (KINAC). Quick verification of the fuel assembly requires the development of a high-quality image reconstruction algorithm that enables image acquisition within a short time. This study examined various tomographic image reconstruction techniques to identify patterns of missing fuel rods accurately. Rotational projection image data sets were obtained for 15 patterns of test fuel rods for 900 seconds using the single-photon emission computed tomography (SPECT) system installed at KINAC. The projection images were acquired every 5° while four 64-channel detectors rotated 90°. The acquired images were reconstructed using the following methods: filtered back-projection, simultaneous iterative reconstruction technique, order-subset simultaneous algebraic reconstruction technique, maximum likelihood expectation maximization (MLEM), and Fast-Iterative Shrinkage-Thresholding algorithm (FISTA). Among the reconstruction algorithms used in this study, the image quality of MLEM showed the best performance, and the image contrast of FISTA showed the highest result. Therefore, the signal-to-noise ratio of the tomographic image was improved using the image reconstruction technique optimized for the YSECT system to verify the patterns of fuel rods. Hence, even for the low-quality measured data with the short-time scan of the SPECT system, this advanced technique is expected to show better discriminability of the patterns of fuel rods in the assembly.

Non-destructive 3D reconstruction of an Hagia Sophia clone mosaic utilizing ultrasonography combined with an accurate motion planning

In the current work the endoscopy and retrieval of mortar covered mosaic patterns, such as the Hagia Sophia ones, is presented. In particular, an appropriate instrumentation is developed combining ultra-sonic tomography and an accurate motion planning. The acquisition of high-response tomographic images is performed utilizing transducers in a linear array through the efficient control of their phase characteristics both in transmit and receive modes. Moreover, an accurate mechanical adaptation is designed in order to move the ultrasonic probe with a con-stant velocity. Then, a sequence of tomographic images is recorded and the 3D endoscopic characteristics of the measured object are extracted via the effective reconstruction of the 3D volume. This device is used on a realistic Hagia Sophia mosaic replica that is covered by a thick mor-tar layer. The evaluated results indicate a complete 3D reconstruction of the hidden mosaic in micrometric resolution, while the inner details of individual tesserae are, also, recovered.

Study of aortic valve using multi slice computed tomography in patients presenting with chest pain.

To determine aortic root dimensions in younger patients presenting with chest pain. The descriptive cross-sectional study was conducted at the Armed Forces Institute of Cardiology and the National Institute of Heart Diseases, Rawalpindi, Pakistan, from September 12, 2018, to March 11, 2019, and comprised patients of either gender aged 18-55 years presenting with chest pain falling into Canadian Cardiovascular Society class I-IV and dyspnoea falling into New York Heart Association class I-IV. Multi-slice computed tomography image acquisition was performed in a single breath-hold of about 5-10 seconds, while electrocardiogram gated synchronised data acquisition was done with 60-100ml contrast. Multiphase data-sets were reconstructed followed by data analysis. Required measurements were recorded with software caliper and tracer. Data was analysed using SPSS 23. Of the 330 patients, 236(71.5%) were males and 94(28.5%) were females. The overall mean age was 45.5±7.9 years. Bicuspid aortic valve was found in 3(0.9%) patients, while 327(99.1%) were tricuspid. Mean aortic valve area was 4.01±0.70cm2, mean aortic annular size was 21.9±2.37mm, sinotubular junction diameter was 23.9±3.45mm, and mean sinotubular junction height was 21.09±2.77mm. The mean diameter at sinuses of valsalva was 33.0±3.99mm. Mean aortic root dimensions and general morphology of the aortic valve was determined to establish normal reference values.

In situ observation with x-ray for tentative exploration of laser beam welding processes for aluminum-based alloys

In recent years, laser processes have taken an ever-increasing market share in the manufacture of components. The development of new, improved beam sources with corresponding systems technology and the decreasing investment costs of the beam sources are important keys to this success. Particularly, high frequency beam oscillation has great potential in laser beam welding and cutting. The main obstacle for the widespread breakthrough of high frequency (HF) beam oscillation is the still insufficient understanding of the underlying physical mechanisms. Gaining a deeper insight is essential for process optimization. The in situ observation with x rays enables the visualization and analysis of these highly dynamic processes inside the workpiece. The goal of the performed experiment described in this paper was to in situ analyze the structural evolution of and defect generation in laser welding beads of different aluminum alloys. A fiber laser (max. 600 W, cw output power) including a beam scanner control system for rapid beam guidance was used. Of general interest was the comparison between static and oscillated beam guidance and the effects on the joining procedure. This paper shows the initial results of the analysis of the melt pool behavior and seam formation as well as the formation of seam irregularities during the laser process. In the simplest case, radiographs were taken, i.e., 2D projections of the x-ray absorption coefficient distribution within a material. Thereby, recordings from 10 000 up to 40 000 fps could be generated. Furthermore, tomoscopies—the continuous acquisition of tomographic (3D) images, up to 100 tomograms per second—could be generated with proven equipment, whose main components are a high-speed rotation stage and a camera system. The findings will help to get a better understanding of keyhole phenomena as well as effects of turbulent melt flow such as pore formation and guide to solutions for preventing them. Hence, initial results of high frequency beam oscillation processes including melt pool degassing and porosity reduction will be shown and discussed.

Development of de-noised image reconstruction technique using Convolutional AutoEncoder for fast monitoring of fuel assemblies

The International Atomic Energy Agency has developed a tomographic imaging system for accomplishing the total fuel rod-by-rod verification time of fuel assemblies within the order of 1–2 h, however, there are still limitations for some fuel types. The aim of this study is to develop a deep learning-based de-noising process resulting in increasing the tomographic image acquisition speed of fuel assembly compared to the conventional techniques. Convolutional AutoEncoder (CAE) was employed for de-noising the low-quality images reconstructed by filtered back-projection (FBP) algorithm. The image data set was constructed by the Monte Carlo method with the FBP and ground truth (GT) images for 511 patterns of missing fuel rods. The de-noising performance of the CAE model was evaluated by comparing the pixel-by-pixel subtracted images between the GT and FBP images and the GT and CAE images; the average differences of the pixel values for the sample image 1, 2, and 3 were 7.7%, 28.0% and 44.7% for the FBP images, and 0.5%, 1.4% and 1.9% for the predicted image, respectively. Even for the FBP images not discriminable the source patterns, the CAE model could successfully estimate the patterns similarly with the GT image.

Computerized Tomography (CT) Updates and Challenges in Diagnosis of Bone Metastases During Prostate Cancer.

Prostate cancer is one of the most common cancers in men. This cancer is often associated with indolent tumors with little or no lethal potential. Some of the patients with aggressive prostate cancer have increased morbidity and early deaths. A major complication in advanced prostate cancer is bone metastasis that mainly results in pain, pathological fractures, and compression of spinal nerves. These complications in turn cause severe pain radiating to the extremities and possibly sensory as well as motor disturbances. Further, in patients with a high risk of metastases, treatment is limited to palliative therapies. Therefore, accurate methods for the detection of bone metastases are essential. Technical advances such as single-photon emission computed tomography/ computed tomography (SPECT/CT) have emerged after the introduction of bone scans. These advanced methods allow tomographic image acquisition and help in attenuation correction with anatomical co-localization. The use of positron emission tomography/CT (PET/CT) scanners is also on the rise. These PET scanners are mainly utilized with 18F-sodium-fluoride (NaF), in order to visualize the skeleton and possible changes. Moreover, NaF PET/CT is associated with higher tracer uptake, increased target-to-background ratio and has a higher spatial resolution. However, these newer technologies have not been adopted in clinical guidelines due to lack of definite evidence in support of their use in bone metastases cases. The present review article is focused on current perspectives and challenges of computerized tomography (CT) applications in cases of bone metastases during prostate cancer.

An assessment of the quality of optical coherence tomography image acquisition.

Optical coherence tomography (OCT) provides excellent image resolution, however OCT optimal acquisition is essential but could be challenging owing to several factors. We sought to assess the quality of OCT pullbacks and identify the causes of suboptimal image acquisition. We evaluated 784 (404 pre-PCI; 380 post-PCI) coronary pullbacks from an anonymized OCT database from our Cardiovascular Imaging Core Laboratory. Imaging of the region-of-interest (ROI-lesion or stented segment plus references) was incomplete in 16.1% pullbacks, caused by pullback starting too proximal (63.7%), inappropriate pullback length (17.1%) and pullback starting too distal (11.4%). The quality of image acquisition was excellent in 36.3% pullbacks; whereas 4% pullbacks were unanalyzable. Pullback quality was most commonly affected by poor blood displacement from inadequate contrast volume (27.4%) or flow (25.6%), followed by artifacts (24.1%). Acquisition mode was 'High-Resolution' (54mm) in 74.4% and 'Survey' (75mm) in 25.6% of cases. The 54mm mode was associated with incomplete ROI imaging (p = 0.020) and inadequate contrast volume (p = 0.035). We observed a substantial frequency of suboptimal image acquisition and identified its causes, most of which can be addressed with minor modifications during the procedure, ultimately improving patient outcomes.

Peeling the Otolith of Fish: Optimal Parameterization for Micro-CT Scanning

In this paper, we aim to provide optimal parameters for micro-computed tomography scans of fish otoliths. We tested fifteen different combinations to sagittae. The images were scaled to Hounsfield units, and segmented in two distinct volumes-of-interest (external and internal). The strategy we applied, for identifying optimum scan settings for otoliths, included analyses of the sinogram, the distribution of the Hounsfield units and the signal-to-noise ratio. Based on these tests, the optimum sets of parameters for the acquisition of tomographic images of sagittal otoilths were 80 kV, 220 microA and 0.5 mm aluminum filter.The method allowed 3D shape analysis, internal and external density distribution, layer-by-layer density segmentation, and a potential objective method to count growth rings in otoliths. It was possible to compare mean densities between species, and we observed a significant difference among them. In addition, there are ontogenic changes, which could be increasing or decreasing the density. In this study, we applied tomography for several otolith analysis, that could be of great interest for future studies in diverse areas that use otoliths as the basic structure of analysis, or represents a new research line called eco-densitometry of otoliths, where tomography could be applied to explore the density within an ecological perspective.

Using X-ray tomoscopy to explore the dynamics of foaming metal

The complex flow of liquid metal in evolving metallic foams is still poorly understood due to difficulties in studying hot and opaque systems. We apply X-ray tomoscopy –the continuous acquisition of tomographic (3D) images– to clarify key dynamic phenomena in liquid aluminium foam such as nucleation and growth, bubble rearrangements, liquid retraction, coalescence and the rupture of films. Each phenomenon takes place on a typical timescale which we cover by obtaining 208 full tomograms per second over a period of up to one minute. An additional data processing algorithm provides information on the 1 ms scale. Here we show that bubble coalescence is not only caused by gravity-induced drainage, as experiments under weightlessness show, and by stresses caused by foam growth, but also by local pressure peaks caused by the blowing agent. Moreover, details of foam expansion and phenomena such as rupture cascades and film thinning before rupture are quantified. These findings allow us to propose a way to obtain foams with smaller and more equally sized bubbles.

Multi-wavelength spatial frequency domain diffuse optical tomography using single-pixel imaging based on lock-in photon counting.

We present a spatial frequency domain (SFD) diffuse optical tomography for simultaneous acquisition of multi-wavelength tomographic images of turbid media. We propose a highly sensitive single-pixel SFD imaging system for simultaneously collecting multi-wavelength spatially modulated reflectance images, instead of using the expensive electron-multiplying charge-coupled device camera that requires switching between the multi-wavelength collections. The single-pixel SFD imaging system using three low-power light sources (455, 532 and 660 nm) that were intensity-modulated by square waves with three different frequencies for frequency encoding, and all the light sources were focused onto one digital micromirror device (DMD) for generating wide-field sinusoidal illumination patterns. Reflected light from the surface of the turbid media was modulated by the other DMD with many sampling patterns before being spatially integrated. Spatially integrated light signals were frequency decoded with a novel highly sensitive lock-in photon counting detection, then multi-wavelength spatially modulated reflectance images were recovered with the single-pixel imaging (SPI) method. We incorporated the two-dimensional discrete cosine transform (DCT) into the SPI method to reduce the number of sampling patterns, and, thereby, the proposed DCT-SPI scheme achieved a fast acquisition of SFD reflectance images that is desired for a dynamic SFD imaging application. Direct current (DC) and alternating current (AC) amplitudes at all the locations on the media surface were extracted from the recovered images. Multi-wavelength tomographic images were reconstructed with an inversion algorithm based on the first-order Rytov approximation of the diffusion equation, using both the extracted DC and AC amplitudes. We performed experiments using a series of tissue simulating phantoms to verify the performances of the proposed approach and compared the experimental results with those using a conventional camera-based SFD imaging system. The results demonstrate that our DCT-SPI based SFD-DOT approach is well suited for simultaneous reconstruction of multi-wavelength tomographic images to pave the way for many SFD imaging applications.

Effect of the software binning and averaging data during microcomputed tomography image acquisition

This study describes the effect of the software binning and data averaging during micro CT volume acquisition, on the assessment of root resorption volumes. The mesial roots (n = 9), after orthodontic tooth movement during 14 days, were scanned, using a micro CT system (9 µm/pixel). All roots were reconstructed and the volumes of the resorption lacunae evaluated. The height and width of the pixels vary according to the parameters (A1, A2, A3, A4, A5, A6, A7, A8, A9) used during the scan. In the root #1 the mean volumes of resorption were similar in A4 and A7; in the root #2 there was no similarity in the mean volumes of resorption in any of the parameters; in root #3 only A4 presented mean volume different from zero (3.05 × 10°). In the root #5, the A1 and A7 presented similar mean volumes and in the A6 and A9 presented near mean volumes. In the root #9 the A1, A4, and A7 presented similar mean volumes and A6 and A9 also had similar mean volumes. Significant difference was detected in the volume of resorption among the roots #2, #5 and #9 (p = 0.04). When analyzing delicate structures such as the roots of rats’ molars, the variation of such parameters will significantly influence the results.

Optical Coherence Tomography as an Adjunct During Carotid Artery Stenting for Carotid Atherosclerotic Disease.

Carotid artery stenting (CAS) has been proven to decrease the risk of stroke in symptomatic patients with moderate/high-grade carotid stenosis; however, there is an increased periprocedural risk of stroke with CAS compared to carotid endarterectomy. The goal of this article is to report the utilization of endovascular optical coherence tomography (OCT) during CAS to aid in the identification of stent malapposition, plaque prolapse, and adjacent residual thrombus that could cause periprocedural stroke. Approval was obtained for endovascular OCT imaging in patients undergoing CAS. Images were obtained before and after stenting. Images were acquired with proximal balloon occlusion and saline to clear luminal blood during acquisition. Atotal of seven patients provided informed consent for imaging. There were no complications during image acquisition or the stenting procedure. Optical coherence tomography imaging revealed free intraluminal red thrombi, fibrous cap dissections, and thin cap fibroatheromas with underlying ulcerative plaques. Plaque herniation through stents was also demonstrated along with thrombus. Poor stent apposition was clearly visible. Optical coherence tomography image acquisition was found to be safe, effective, and to provide valuable information about plaque morphology and stent-vessel interactions. The role of perioperative anticoagulation after stenting should be re-evaluated given the new findings. Astudy comparing CAS with and without OCT with aclinical primary outcome such as ipsilateral stroke could help determine if OCT is an innovative tool to guide stenting and antithrombotic management.

Investigating spontaneous retinal venous pulsation using Doppler optical coherence tomography

We demonstrate the advantages of optical coherence tomography (OCT) imaging for investigation of spontaneous retinal venous pulsation (SRVP). The pulsatile changes in venous vessel caliber are analyzed qualitatively and quantitatively using conventional intensity-based OCT as well as the functional extension Doppler OCT (DOCT). Single-channel and double-channel line scanning protocols of our multi-channel OCT prototype are employed to investigate venous pulsatile caliber oscillations as well as venous flow pulsatility in the eyes of healthy volunteers. A comparison to recordings of scanning laser ophthalmoscopy (SLO) – a standard en-face imaging modality for evaluation of SRVP – is provided, emphasizing the advantages of tomographic image acquisition. To the best of our knowledge, this is the first quantitative time-resolved investigation of SRVP and associated retinal perfusion characteristics using OCT.

100.05 An Assessment of the Quality of Optical Coherence Tomography Image Acquisition: Are We Doing the Basics Right?

Optical coherence tomography (OCT) provides excellent image resolution but requires blood displacement with contrast injection for image acquisition, as opposed to other intravascular imaging modalities. In addition, there are other small differences that make the process more challenging, such as