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Introduction and objectives: patients with long, sequential and diffuse coronary lesions who undergo a percutaneous coronary intervention remain at a high risk of suffering cardiovascular events despite the improved safety and efficacy of the new drug-eluting stents. The objective of this study was to analyze the utility of SyncVision/iFR-guided revascularization (SyncVision version 4.1.0.5, Philips Volcano, Belgium) in this type of lesions. Methods: Randomized, multicenter, controlled, and open-label trial designed to compare SyncVision/iFR-guided and angiography-guided revascularizations in patients with long, sequential or diffuse significant angiographic coronary stenosis (ClinicalTrials.gov identifier: NCT04283734). A total of 100 patients will be randomized (1:1, no stratification). The primary endpoint is the average length of the stent implanted. The secondary endpoint is a composite of cardiac death, myocardial infarction, definitive or probable stent thrombosis, new target lesion revascularization or new target lesion failure; and the presence of residual ischemia as seen on single-photon emission computed tomography at the 6-month follow-up. Patients will be followed for 12 months after the procedure. Results: The trial is currently in the recruitment phase, and it has already recruited the first 7 patients. We expect to complete the recruitment phase by February 2021 and the follow-up by February 2022. Conclusions: The iLARDI study is the first randomized trial to assess the potential utility of SyncVision-guided revascularization in long, sequential and diffuse coronary lesions.

Background and purpose Deep brain stimulation of the thalamus is an effective treatment for multiple neurological disorders. The centromedian and parafascicular nuclei are recently emerging targets for multiple conditions, such as epilepsy and Tourette syndrome; however, their limited visibility on conventional magnetic resonance imaging sequences has been a major obstacle. The goal of this study was to demonstrate the feasibility of a high-resolution and high-contrast targeting sequence for centromedian-parafascicular deep brain stimulation using a recently described magnetic resonance imaging sequence, three-dimensional edge-enhancing gradient echo. Methods The three-dimensional edge-enhancing gradient echo sequence was performed on a normal volunteer for a total of six acquisitions. Multi-image co-registration and averaging was performed by first co-registering each of the six scans and then averaging to produce an edge-enhancing gradient echo-multi-image co-registration and averaging scan. The averaging was also performed for two, three, four and five scans to assess the change in the signal-to-noise ratio and identify the ideal balance of image quality and scan time. Results The edge-enhancing gradient echo-multi-image co-registration and averaging scan allowed clear boundary delineation of the centromedian and parafascicular nuclei. The signal-to-noise ratio increased as a function of increasing scan number, but the added gain was small beyond four scans for the imaging parameters used in this study. Conclusions The recently described three-dimensional edge-enhancing gradient echo sequence provides an easily implementable approach, using widely available magnetic resonance imaging technology without complex post-processing techniques, to delineate centromedian and parafascicular nuclei for deep brain stimulation targeting.

Magnetic resonance imaging (MRI) is a widely used non-invasive methodology for both preclinical and clinical studies. However, MRI lacks molecular specificity. Molecular contrast agents for MRI would be highly beneficial for detecting specific pathological lesions and quantitatively evaluating therapeutic efficacy in vivo. In this study, an optimized Magnetization Prepared—RApid Gradient Echo (MP-RAGE) with 2 inversion times called MP2RAGE combined with advanced image co-registration is presented as an effective non-invasive methodology to quantitatively detect T1 MR contrast agents. The optimized MP2RAGE produced high quality in vivo mouse brain T1 (or R1 = 1/T1) map with high spatial resolution, 160 × 160 × 160 µm3 voxel at 9.4 T. Test–retest signal to noise was > 20 for most voxels. Extremely small iron oxide nanoparticles (ESIONPs) having 3 nm core size and 11 nm hydrodynamic radius after polyethylene glycol (PEG) coating were intracranially injected into mouse brain and detected as a proof-of-concept. Two independent MP2RAGE MR scans were performed pre- and post-injection of ESIONPs followed by advanced image co-registration. The comparison of two T1 (or R1) maps after image co-registration provided precise and quantitative assessment of the effects of the injected ESIONPs at each voxel. The proposed MR protocol has potential for future use in the detection of T1 molecular contrast agents.

Introduction: During deep brain stimulation (DBS) surgery, computed tomography (CT) and magnetic resonance imaging (MRI) scans need to be co-registered or fused. Image fusion is associated with the error that can distort the location of anatomical structures. Co-registration in DBS surgery is usually performed automatically by proprietary software; the amount of error during this process is not well understood. Here, our goal is to quantify the error during automated image co-registration with FrameLink™, a commonly used software for DBS planning and clinical research. Methods: This is a single-center retrospective study at a quaternary care referral center, comparing CT and MR imaging co-registration for a consecutive series of patients over a 12-month period. We collected CT images and MRI scans for 22 patients with Parkinson’s disease requiring placement of DBS. Anatomical landmarks were located on CT images and MRI scans using a novel image analysis algorithm that included a method for capturing the potential error inherent in the image standardization step of the analysis. The distance between the anatomical landmarks was measured, and the error was found by averaging the distances across all patients. Results: The average error during co-registration was 1.25 mm. This error was significantly larger than the error resulting from image standardization (0.19 mm) and was worse in the anterior-posterior direction. Conclusions: The image fusion errors found in this analysis were nontrivial. Although the estimated error may be inflated, it is sig­nificant enough that users must be aware of this potential inaccuracy, and developers of proprietary software should provide details about the magnitude and direction of co-registration errors.

The estimation of forest attributes at the local scale as well as in wall-to-wall approaches benefits from the integration of remote sensing data such as airborne laser scanning (ALS). A poor level...

Background Intravascular ultrasound (IVUS) provides endoluminal views and cross-sectional images of carotid arteries but lacks overview of vascular territory provided by angiography. Co-registration of IVUS with angiographic images may provide the potential to navigate both imaging modalities in a synchronous manner. The objective of this study is to evaluate the feasibility and accuracy of co-registering both imaging modalities in the carotid vasculature of the neck. Methods Fourteen patients with 15 cervical carotid artery lesions underwent angiography and subsequent treatment. In each case, an IVUS catheter was advanced to the target lesion and a reference angiography sequence was acquired. This was followed by an electrocardiography-triggered fluoroscopy sequence that was initiated upon IVUS catheter pullback. IVUS data collected during pullback were registered with fluoroscopy and evaluated for error and clinical usability. Results A total of 32 landmarks were identified that demonstrated reasonable agreement during IVUS–angiography co-registration. There was a mean registration error distance of 3.36 mm (SD 2.82 mm) between targets. The longitudinal extent and severity of the disease through the target segment could be easily evaluated after co-registration. Conclusion Semiautomatic tracking and co-registration of angiography and IVUS is a new technology and has the potential to increase the use of IVUS in carotid disease and to proivde the opportunity to optimize procedural outcomes.

Image registration is an important preprocessing step prior to detecting changes using multi-temporal image data, which is increasingly accomplished using automated methods. In high spatial resolution imagery, shadows represent a major source of illumination variation, which can reduce the performance of automated registration routines. This study evaluates the statistical relationship between shadow presence and image registration accuracy, and whether masking and normalizing shadows leads to improved automatic registration results. Eighty-eight bitemporal aerial image pairs were co-registered using software called Scale Invariant Features Transform (SIFT) and Random Sample Consensus (RANSAC) Alignment (SARA). Co-registration accuracy was assessed at different levels of shadow coverage and shadow movement within the images. The primary outcomes of this study are (1) the amount of shadow in a multi-temporal image pair is correlated with the accuracy/success of automatic co-registration; (2) masking out shadows prior to match point select does not improve the success of image-to-image co-registration; and (3) normalizing or brightening shadows can help match point routines find more match points and therefore improve performance of automatic co-registration. Normalizing shadows via a standard linear correction provided the most reliable co-registration results in image pairs containing substantial amounts of relative shadow movement, but had minimal effect for pairs with stationary shadows.

Stereotactic radiosurgery (SRS) or radiotherapy (SRT) is commonly used to treat brain metastasis (BM). While effective in achieving tumor control, a significant number of BM patients exhibit lesion growth on follow-up MR imaging after SRS which cannot reliably distinguish between tumor growth, radiation necrosis (RN) or a mixture of both. SRS retreatment is a therapeutic option for tumor regrowth but contraindicated for RN. Here, we describe an instructive case of MRI progression of a breast BM previously treated by SRS where [18F] fludeoxyglucose-positron emission tomography (FDG-PET) proved useful to anatomically delineate metabolically active tumor from RN for re-treatment planning. Post-treatment FDG-PET and MRI studies indicated decreased uptake and enhancement respectively following treatment. This case study underscores the biological heterogeneity underlying MRI based BM progression after prior SRS and the potential utility of FDG-PET to guide treatment planning for repeat SRS.

Intravascular imaging using both intravascular ultrasound (IVUS) and optical coherence tomography (OCT) have become important tools in the Interventional Cardiologists armamentarium. However, in some centers, intravascular imaging is not widely employed. A number of reasons for this may exist, including lack of training in the use of intravascular imaging. Co-registration with angiography may be a helpful tool for those beginning to use both IVUS and OCT in the cath lab, and may reduce the learning curve associated with its use. For experienced operators, co-registration can shorten procedure time and lessen contrast use which may be particularly important when performing complex or multivessel PCI. As a research tool, co-registration can allow for accurate comparison of interval intravascular images. In this review, we will discuss how to acquire co-registered images using both IVUS and OCT systems, and the potential advantages of this technology over non-co-registered images, and indeed angiography alone.

Politeknik Caltex Riau (PCR) adalah sebuah perguruan tinggi di Pekanbaru, Riau. PCR memiliki proses bisnis, salah satunya adalah Carry Over (CO) atau semester pendek. Proses bisnis CO saat ini tidak sepenuhnya dilakuka dengan optimal, seperti penjadwalan, pendaftaran CO untuk siswa, dan distribusi honor untuk dosen dan atau laboran. Ini menunjukkan bahwa proses bisnis saat ini belum efisien dan dapat mempengaruhi proses bisnis organisasi secara keseluruhan. Olehkarena itu, proses bisnis CO saat ini perlu ditingkatkan. Tujuannya adalah untuk meningkatkan proses untuk layanan CO yang lebih baik bagi mahasiswa. Metode yang digunakan untuk perbaikan adalah Business Process Improvement (BPI), dengan mengimplementasikan salah satu alatnya yang disebut streamlining. Jenis streamlining yang diterapkan dalam peningkatan proses bisnis CO antara lain upgrading, standardization, bureaucracy elimination, dan process cycle-time reduction. Setelah perbaikan proses, ada proses layanan CO yang lebih ringkas dengan total 17 jumlah prosesdari 19 jumlah prosessebelumnya. Peningkatan proses CO juga didukung oleh pemanfaatan Sistem Informasi Akademik PCR.

Introduction Intravascular ultrasound (IVUS) is a useful adjunct to guide percutaneous coronary intervention (PCI). Correlating IVUS images with angiographic findings can be challenging. We evaluated the utility of a novel co-registration system for IVUS and coronary angiography. Methods and results A 3-D virtual catheter trajectory was constructed from separate angiographic imaging runs using bespoke software. Intravascular ultrasound images were obtained using a commercially available mechanical rotational transducer with motorized pullback. Co-registration of ultrasound and angiographic images was then performed retrospectively based on the length of pullback, the 3-D trajectory and the start position of the catheter. Validation was performed in a spherical phantom model and in vivo in the coronary circulation of patients undergoing coronary angiography and intravascular imaging for clinical purposes. 111 paired angiographic and IVUS runs were performed in 3 phantom models. The differences between the reference length and the length measured on the 3D reconstructed path was −0.01 ± 0.40 mm. Intra-observer variability was 0.4%. We enrolled 25 patients in 3 European hospitals and performed 35 co-registration attempts with an 86% success rate. 71 landmarks were selected by the first operator, 68 by the second. Differences between angiographic and IVUS landmarks were −0.22 ± 0.72 mm and 0.05 ± 1.01 mm, respectively. Inter-observer variability was 0.23 ± 0.63 mm. Conclusion We present a novel method for the co-registration of IVUS and coronary angiographic images. This system performed well in a phantom model and using images obtained from the human coronary circulation. Classifications Innovation, intravascular ultrasound, other technique

Mass spectrometry imaging (MSI) is an analytical technique for the unlabeled and multiplex imaging of molecules in biological tissue sections. It therefore enables the spatial and molecular annotations of tissues complementary to histology. It has already been shown that MSI can guide subsequent material isolation technologies such as laser microdissection (LMD) to enable a more in-depth molecular characterization of MSI-highlighted tissue regions. However, with MSI now reaching spatial resolutions at the single-cell scale, there is a need for a precise co-registration between MSI and the LMD. As proof-of-principle, MSI of lipids was performed on a breast cancer tissue followed by a segmentation of the data to detect molecularly distinct segments within its tumor areas. After image processing of the segmentation results, the coordinates of the MSI-detected segments were passed to the LMD system by three co-registration steps. The errors of each co-registration step were quantified and the total error was found to be less than 13 μm. With this link established, MSI data can now accurately guide LMD to excise MSI-defined regions of interest for subsequent extract-based analyses. In our example, the excised tissue material was then subjected to ultrasensitive microproteomics in order to determine predominant molecular mechanisms in each of the MSI-highlighted intratumor segments. This work shows how the strengths of MSI, histology, and extract-based omics can be combined to enable a more comprehensive molecular characterization of in situ biological processes. Electronic supplementary material The online version of this article (10.1007/s00216-019-01983-z) contains supplementary material, which is available to authorized users.

As lipid composition of atherosclerotic plaques is considered to be one of the primary indicators for plaque vulnerability, a diagnostic modality that can sensitively evaluate their necrotic core is highly desirable in atherosclerosis imaging. In this regard, intravascular photoacoustic (IVPA) imaging is an emerging plaque detection modality that provides lipid-specific chemical information of arterial walls. Within the near-infrared window, a 1210-nm optical source is usually chosen for IVPA applications because lipid exhibits a strong absorption peak at that wavelength. However, other arterial tissues also show some degree of absorption near 1210 nm and generate undesirable interfering PA signals. In this study, a novel wavelength-modulated Intravascular Differential Photoacoustic Radar (IV-DPAR) modality was introduced as an interference-free detection technique for a more accurate and reliable diagnosis of plaque progression. By using two low-power continuous-wave laser diodes in a differential manner, IV-DPAR could efficiently suppress undesirable absorptions and system noise, while dramatically improving system sensitivity and specificity to cholesterol, the primary ingredient of plaque necrotic core. When co-registered with intravascular ultrasound imaging, IV-DPAR could sensitively locate and characterize the lipid contents of plaques in human atherosclerotic arteries, regardless of their size and depth.

Repeat station imaging (RSI) is a method for specialized image collection and co-registration that facilitates rapid change detection with aerial imagery for time-critical analyses. Our previously ...

Purpose: Multiplex staining allows molecular co-localization analysis of same cell or tissue sections and maximizes the amount of data acquired from individual samples. We developed a non-linear registration framework for automated alignment of whole mount multiplexed histology images of prostate cancer. To achieve a precise automatic fit of bleached and restained high resolution tissue samples, a patch-based approach is proposed to improve annotation speed and analysis. Methods: The three-step co-registration process begins with a coarse low-resolution registration of the IHC stained image to the fixed H&E-stained image. The initial registration is then refined separately for each high-resolution patch using a smaller search window. Finally, registered patches are stitched back together using speeded up robust features (SURF). We apply the method to five multiplex whole mount prostate histology slides. To determine its effectiveness, we compare the automatic registration to the initial coarse registration and a manual control point based-method varying the number of control points. Results: For the control point-based approach, 25, 50, and 100 manually placed set landmarks resulted in a decrease of - 76.20%, -75.9% and -75.48% of the root mean squared error (RMSE), respectively. Compared to the initial registration an improvement of -76.29% of RMSE can be seen, illustrating the potential benefits of a patch-based automatic approach. Conclusion: The proposed method achieved excellent registration of the IHC to the input image. The automated method for registration of multiplexed histology images achieves high accuracy in shorter time and with greater reproducibility than conventional registration approaches and semi-automatic control points without the need for time consuming and subjective manual control-point setting. The accuracy of the fit especially improves in complex areas close to tissue tears and folds.

Transcranial magnetic stimulation (TMS) excites neurons in the cortex, and neural activity can be simultaneously recorded using electroencephalography (EEG). However, TMS-evoked EEG potentials (TEPs) do not only reflect transcranial neural stimulation as they can be contaminated by artifacts. Over the last two decades, significant developments in EEG amplifiers, TMS-compatible technology, customized hardware and open source software have enabled researchers to develop approaches which can substantially reduce TMS-induced artifacts. In TMS-EEG experiments, various physiological and external occurrences have been identified and attempts have been made to minimize or remove them using online techniques. Despite these advances, technological issues and methodological constraints prevent straightforward recordings of early TEPs components. To the best of our knowledge, there is no review on both TMS-EEG artifacts and EEG technologies in the literature to-date. Our survey aims to provide an overview of research studies in this field over the last 40 years. We review TMS-EEG artifacts, their sources and their waveforms and present the state-of-the-art in EEG technologies and front-end characteristics. We also propose a synchronization toolbox for TMS-EEG laboratories. We then review subject preparation frameworks and online artifacts reduction maneuvers for improving data acquisition and conclude by outlining open challenges and future research directions in the field.

In this work, a novel approach for the correction of misregistration errors in sequences of Terrain Observation with Progressive Scan (TOPS) Sentinel-1 SAR data is presented. The method represents a further evolution of the Enhanced Spectral Diversity (ESD) approaches. Remarkably, the developed algorithm is almost insensitive to the presence of large azimuth ground displacements due, for instance, to massive earthquakes, volcanic eruptions or glacier movements. Indeed, in such non-stationary contexts, the conventional ESD and network ESD approaches for the SAR TOPS data co-registration reveals problematic being co-registration errors and azimuth ground deformation components mixed out. Preliminary experiments conducted on a set of TOP SAR data related to the area hit by the Ridgecrest earthquake MW 7.1, California, on July 04 2019 confirm the validity of the theoretical framework.

Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Spanish Ministry of Science, Innovation and Universities Instituto de Salud Carlos III Background. Dilation of the aortic root is a key feature of Marfan syndrome and it is related to the occurrence of aortic events and death. On top of maximum diameter, rapid annual growth rate is suggested by guidelines for indication of aortic root replacement. Current gold-standard for aortic root diameter assessment is manual quantification on multiplanar reformatted 3D computed tomography (CT) or magnetic resonance angiogram. However, inter- and intra-observer reproducibility are limited and different measurement methods, i.e. cusp-to-cusp and cusp-to-commissure, may be used in different clinical centres, leading to difficulties in the clinical assessment of progressive dilation. Purpose. We aimed to test whether aortic root growth rate during follow-up can be reliably quantified by semi-automatic co-registration of two CT angiograms. Methods. Seven Marfan syndrome patients, free from previous aortic surgery, with a total of 11 pairs of CT were identified. Manual assessment of six aortic root diameters (right-non coronary -RN- , right-left -RL- and left-non coronary -LN- cusp-to-cusp and R, L and N cusp-to-commissure) was obtained from all CTs by an experienced researcher blind to semi-automatic results. The thoracic aorta and the outflow tract were semi-automatically segmented in the baseline CT and commissure and cusps were manually located. A 10 mm-thick region of interest containing the aortic wall was automatically generated from segmentation boundary. Co-registration was obtained with three, fully-automatic steps. Firstly, baseline and follow-up CT scans were aligned by means of a rigid registration. Then, scans were co-registered with multi-resolution affine followed by b-spline non-rigid registrations based on mutual information metric. The transformation pertaining to the location of baseline commissure and cusps points was used to locate the same points in the follow-up scan (Fig. 1 top). Results. Follow-up duration was 35 ± 22 (range 12-70.3) months. Automatic quantification of diameter growth during the follow-up was obtained in 62 out of 66 (94%) diameter comparisons. High Pearson correlation coefficients (R) and ICC were found between manual and semi-automatic assessment of growth rate, both for cusp-to-cusp and cusp-to-commissure diameters: R = 0.727 and ICC = 0.678 for RN; R = 0.822 and ICC = 0.602 for RL; R = 0.648 and ICC = 0.668 for LN; R = 0.726 and ICC = 0.711 for R; R = 0.911 and ICC = 0.895 for L and R = 0.553 and ICC = 0.482 for N. Scatter and Bland-Altman plots for all growth rates (Fig. 1) confirmed very good correlation (R = 0.810) but a slight tendency (R=-0.270) for underestimation at high growth rate. No correlation was found between follow-up duration and difference between techniques (R = 0.06). Conclusions. Semi-automatic quantification of aortic root growth rate by co-registration of pairs of CT angiograms is feasible for follow-up as short as one year. Larger studies are needed to confirm these preliminary data. Abstract Figure. CT measurements. Automatic vs manual.

Imaging procedures are fundamental to disease diagnosis and prognosis, along with intervention evaluation and monitoring progression. Quantitative comparison and integration of information from different image sets require image coregistration, a process typically performed manually by clinicians. Automated and semi-automated procedures rely upon features that require extensive pre-processing or may not be visible and, as such, are not universally applicable across acquisitions and modalities, limiting applicability. We present a simple yet reliable fully-automated method that registers tomographic vascular images based only on lumen contours. The results both in multimodal and pre-/post-intervention datasets demonstrated the flexibility and robustness of our method. Excellent agreement was found between method results and manual longitudinal coregistration ($0.23\pm 0.20$ mm). Rotational co-registration accuracy was also high $(8.1^{\circ}\pm 8.0^{\circ})$, but required visible fiduciary landmarks; in the absence of such, accuracy decreased to $61.3^{\circ}\pm 66.4^{\circ}$. Sensitivity analyses indicate that, while care must be taken when overlapping segments are very short or lacking variability, lumen-based vascular image co-registration offers a robust, straightforward, and widely applicable approach.

In this paper, we propose a totally unsupervised procedure to cope with the residual local misalignment between a higher-resolution panchromatic (Pan) image and a series of lower-resolution multispectral (MS) bands, preliminarily interpolated to the pixel size of Pan. The proposed method exploits the different resolutions of the MS and Pan datasets to force the former to match a lowpass version of the latter. Specifically, the space-varying residue of the multivariate regression between resampled MS bands and lowpass-filtered Pan image, which locally measures the extent of MS-to-Pan misalignment, is injected into each the MS bands, after being weighted by the pixel-varying multiplicative injection gain of each band. Tests on a GeoEye-1 image, with space-varying shifts, highlight improvements in the spatial alignment.

Abstract We propose the co-registration of local laser profile segments to high resolution Digital Terrain Models (DTMs) as an approach for obtaining seasonal CO2 ice cover height variations on Mars. The co-registration is parameterized in instantaneous MOLA pointing angles involving a rigorous laser altimeter geolocation model. Thereby, the height bias of the MOLA footprint produced by the pointing bias could be compensated through an iterative process. The feasibility and advantages of this method are tested in an example region. The ultimate goal is to apply this method to Mars Orbiter Laser Altimeter (MOLA), SHAllow RADar (SHARAD) radar altimetry and high-resolution stereoscopic DTMs to generate long-term seasonal height change time series at the Martian poles with high spatial and temporal resolution. 1 Introduction The dynamic growth and retreat of polar CO2 frost at the Martian poles has always been one of the focuses of planetary scientists [1, 2, 3]. Accurate measurements of seasonal and long-term elevation and volume changes can serve as important constraints in Mars climate models, help tap into the density evolution of the CO2 snow once combined with gravity measurements, and constrain the degree of stability of the polar deposits. The commonly-used approach to this problem is the cross-over analysis of the laser altimetry profiles, but this method may suffer from significant interpolation errors when spacing between footprints is large, also residual pointing, timing and orbit error may translate into lateral shifts of the laser profiles and further undermine the results. Here, we propose and validate the local co-registration between laser profile segments and high resolution DTMs from stereo pairs as a solution to these limitations. 2 Data 2.1 MOLA records The MOLA Precision Experimental Data Record (PEDR) dataset features a total of 8505 profiles, acquired in the mapping and extended phases of Mars Global Surveyor (MGS) from February, 1999 to May, 2001, which spanned approximately a full Martian year [1]. The PEDR dataset was processed using MGS orbit trajectory model and a Mars rotational model by GSFC dating back to 2003. Therefore, we have incorporated a refined orbit model from [4] and IAU2015 Mars rotational model [5] in the MOLA geolocation reprocessing. Meanwhile, to account for the special relativity effect, the pointing aberration correction has also been taken care of in the reprocessing [6]. 2.2 HRSC DTMs The High Resolution Stereo Camera (HRSC) is a pushbroom camera onboard the European Space Agency (ESA) spacecraft Mars Express. A total of 34 HRSC DTM tiles are adopted which feature a grid size of 50 m and covers the majority of the Martian South Pole [7]. 3 Methods First, the reprocessed MOLA profiles are self-registered to each other to form a coherent reference in the Martian South Pole [8, 9]. Subsequently, individual HRSC DTM tiles have been aligned to the MOLA reference data and mosaiced to a self-consistent reference for the co-registration. The co-registration of the reprocessed MOLA profiles to the aligned HRSC DTM mosaic is setup by compensating for two alignment angles of the boresight and height which incorporates an analytical laser altimeter geolocation model. The benefit is that the height offset induced by bias in pointing can be simultaneously compensated during the iterative co-registration process. The height differences with respect to the DTM mosaic at either footprint, cross-overs, or pseudo cross-overs are assigned as the height corrections from the local co-registration process using segmented profiles centered at these feature points. Here, pseudo cross-overs are DTM-based and formed by two track segments that do not have to actually intersect, substantially increasing the available number of cross-overs [10]. Then, CO2 height change time series are obtained by median-binning those temporal height differences with the uncertainty quantified by scaled median absolute deviation. To get rid of a temporal systematic error, the acquired temporal trend is subtracted from the one at 60°S annulus which features unchanging topography. 4 Results Figure 1: Results using height differences at footprints before the adoption of the local co-registration procedure (“F_LC”, red line, bottom) and comparison to previous literature (lime and aqua lines). Figure 2: Results using height differences at footprints after the adoption of the local co-registration procedure (“F_LC”, red line, bottom) and comparison to previous literature (lime and aqua lines). A test has been carried out at an example region situated right on the residual ice cap where largest peak-to-peak height variation would be expected. The uncertainty of the derived height change time series using height differences at footprints decreased from ~2 m to ~0.5 m after the adoption of the local co-registration procedure, roughly a fourfold enhancement (Figures 1 and 2). The maximum height fluctuation is estimated at ~2.5 m which is similar to that of Aharonson et al. (2004) [2]. The suspicious off-season accumulation pointed out by previous results using MOLA has not been resolved. While a sharp pit-shaped feature of ~1 m depth centered at solar longitude 210° is observed. Similar results have been obtained using height differences at cross-overs and pseudo cross-overs. As a byproduct of the co-registration process, MOLA alignment angles have also been examined to follow some specific temporal patterns. 5 Summary We show the feasibility and merits of the local co-registration strategy in the application of retrieving height changes at either footprints, cross-overs, or pseudo cross-overs. As for the next step, we will put the SHARAD radar altimetry and reflectometry into test [11]. Combined with the MOLA laser altimetry, long-term CO2 height change time series spanning two decades could possibly be retrieved. Apart from height change mapping, the proposed method could also be readily adapted to the tidal Love number measuring, orbit refinement with so called “direct altimetry” [12] and others. Acknowledgements This work was supported by a research grant from Helmholtz Association and German Aerospace Center (DLR). We acknowledge the work by the MOLA and HRSC instrument and science teams. References [1] Smith et al.,Science, 2001, 294, 2141-2146. [2] Aharonson et al., JGRPlanets, 2004, 109(E5). [3] Genova, ActaAstronaut., 2020, 166, 317-329. [4] Konopliv et al., Icarus, 2006, 182, 23-50. [5] Konopliv et al., Icarus, 2016, 274, 253-260. [6] Xiao et al., Submitted to JoG. [7] Putri et al., PSS, 2019, 174, 43-55. [8] Stark et al., EPSC2018, Contrib. No. 890. [9] Stark et al., GRL, 2015, 429, 7881-7889. [10] Barker et al., Icarus, 2016, 273, 346-355. [11] Steinbrügge et al., LPSC2019, LPI Contrib. No. 2132. [12] Goossens et al., Icarus, 2020, 336, 113454.

OBJECTIVES Transcatheter mitral valve-in-valve (TMViV) implantation is an alternative treatment to surgery for high-risk patients with degenerated bioprosthetic mitral valves. Some types of bioprostheses are fluoroscopically translucent, resulting in an ‘invisible’ target deployment area. In this study, we describe the feasibility and outcomes of this procedure using intraoperative fusion of transoesophageal echocardiography (TEE) and live fluoroscopy to facilitate valve deployment in cases of invisible bioprosthetic valves. METHODS We reviewed all TMViV implantations at our centre from July 2014 to July 2019. Patient, procedure and outcome details were compared between those with a visible bioprosthesis (N = 22) to those with an invisible one (N = 12). Intra-operative TEE and live Fluoroscopy co-registration were used for real-time guidance for all invisible targets. RESULTS All valve implantations were completed successfully in both groups without cardiovascular injury, valve migration or left ventricular outflow-tract obstruction. Technical success was 100% in both groups. One-year survival was 83% [95% confidence interval (CI) 70–96] for the entire cohort, with 79% (95% CI 63–100) survival for the visible group and 92% (95% CI 77–100) for the invisible group. Probability of 1-year survival free from mitral valve reintervention, significant valve dysfunction, stroke or myocardial infraction was 78% (95% CI 63–93) for all patients whereby the probability was 72% (95% CI 54–97) in the visible group and 80% (95% CI 59–100) for the invisible group. CONCLUSIONS The use of intraoperative TEE and live fluoroscopy image fusion facilitates accurate TMViV among patients with a fluoroscopically invisible target-landing zone.

Registration or matching process aims to find the misalignment between two or more images concerning the same area to detect the values of the mapping matrix in order to transform interest points in one image to its correspondence in the others. This paper presents a dynamic approach aiming to improve the performance of the registration process for synthetic aperture radar (SAR) images. First, the noise resulting from the capturing process is reduced by using a smoothing filter based on kernel-gaussian to reduce the amplification of noise. Then; a combination of two area- based matching (ABM) methods is used. The first method is carried out using Crosscorrelation approach, acting as coarse registration step. The second method is achieved by using regular step gradient descent (RSGD) optimizer, acting as fine registration step. Evaluation of the performance concerning the proposed manner is achieved by comparing to the state-of-the art detectors as Harris, Shi-Tomasi, and Features from Accelerated Segment Test (FAST) detectors. Metric factors to achieve the comparison are mean square error (MSE) and peak signal-to-noise ratio (PSNR) between the input images. Results demonstrate a highly performance for the proposed method compared to the others where it has a high robustness and minimizes the noise of the input image.

Magnetoencephalography (MEG) is a neuroimaging technique that accurately captures the rapid (sub-millisecond) activity of neuronal populations. Interpretation of functional data from MEG relies upon registration to the participant’s anatomical MRI. The key remaining step is to transform the participant’s MRI into the MEG head coordinate space. Although both automated and manual approaches to co-registration are available, the relative accuracy of two approaches has not been systematically evaluated. The goal of the present study was to compare the accuracy of manual and automated co-registration. Resting MEG and T1-weighted MRI data were collected from 90 participants. Automated and manual co-registration were performed on the same subjects, and the inter-method reliability of the two methods assessed using the intra-class correlation. Median co-registration error for both methods was within acceptable limits. Inter-method reliability was in the “good” range for co-registration error, and the “good” to “excellent” range for translation and rotation. These results suggest that the output of the automated co-registration procedure is comparable to that achieved using manual co-registration.

Intravascular optical coherence tomography (IVOCT) provides high-resolution images of coronary calcifications and detailed measurements of acute stent deployment following stent implantation. Since pre- and post-stent IVOCT image “pull-back” acquisitions start from different locations, registration of corresponding pullbacks is needed for assessing treatment outcomes. In particular, we are interested in assessing finite element model (FEM) prediction of lumen gain following stenting, requiring registration. We used deep learning to segment calcifications in corresponding pre- and post-stent IVOCT pullbacks. We created 1D representations of calcium thickness as a function of the angle of the helical IVOCT scans. Registration of two scans was done by maximizing the cross correlation of these two 1D representations. Registration was accurate, as determined by visual comparisons of 2D image frames. We used our pre-stent calcification segmentations to create a lesion-specific FEM, which took into account balloon size, balloon pressure, and stent measurements. We then compared simulated lumen gain from FEM analysis to actual stent deployment results. Actual lumen gain across ~200 registered pre and post-stent images was 1.52 ± 0.51, while FEM prediction was 1.43 ± 0.41. Comparison between actual and FEM results showed no significant difference (p < 0.001), suggesting accurate prediction of FEM modeling. Registered image data showed good visual agreement regarding lumen gain and stent strut malapposition. Hence, we have developed a platform for evaluation of FEM prediction of lumen gain. This platform can be used to guide development of FEM prediction software, which could ultimately help physicians with stent treatment planning of calcified lesions.

A multi-modal system with dual-channel fluorescence microscopy and high-resolution optical coherence tomography was developed to enable the co-registration of structural and functional information. The system’s performance was demonstrated with microscopic beads sandwiched between multi-layer tapes.

High-Resolution Topography (HRT) data sets are becoming increasingly available, improving our ability and opportunities to monitor geomorphic changes through multi-temporal Digital Terrain Models (DTMs). The use of repeated topographic surveys enables inferring the sediment dynamics of hazardous geomorphic processes such as floods, debris flows, and landslides, and allows us to derive important information on the risks often associated with these processes. The topographic surveying platforms, georeferencing systems, and processing tools have seen important developments in the last two decades, in particular Light Detection And Ranging (LiDAR) technology used in Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS). Moreover, HRT data, produced through these techniques, changed a lot in terms of point cloud density, accuracy and precision over time. Therefore, old "legacy" data sets and recent surveys can often show comparison problems, especially when multi-temporal data are not homogeneous in terms of quality and uncertainties. In this context, data co-registration should be used to guarantee the coherence among multi-temporal surveys, minimizing, on stable areas, the distance between corresponding points acquired at different epochs. Although several studies highlight that this process is fundamental to properly compare multi-temporal DTMs, it is often not addressed in LiDAR post-processing workflows. In this paper we focus on the alignment of multi-temporal surveys in a topographically complex and rugged environment as the Moscardo debris-flow catchment (Eastern Italian Alps), testing various co-registration methods to align multi-temporal ALS point clouds (i.e. years 2003, 2009 and 2013) and the derived DTMs. In particular, we tested the pairwise registration with manual correspondences, the Iterative Closest Point (ICP) algorithm and a mathematical model that allows aligning simultaneously a generic number of point clouds, the so-called Generalized Procrustes Analysis (GPA), also in its GPA-ICP variant. Then, to correct the possible small inaccuracies generated from the gridding interpolation process, a custom-developed DTM co-registration tool (GRD-CoReg) was used to align gridded data. Both alignment phases (i.e. at point cloud and DTM level) proved to be fundamental and allowed us to obtain proper and reliable DTMs of Difference (DoDs), useful to quantify the debris mobilized and to detect the spatial and temporal patterns of catchment-scale erosion and deposition. The consistency of DoDs data was verified through the comparison between the erosion estimate of DoDs and the volumes of debris-flow events measured by the monitoring station close to the Moscardo torrent catchment outlet. The GPA-ICP algorithm followed by the GRD-CoReg tool proved to be the most effective solution for improving DoDs results with a decrease of systematic trend due to vertical and horizontal uncertainties between surveys, especially at steep slopes. The net volume difference (i.e. the sediment output from the catchment) of the 2003-2013 period changed from 3,237,896 m to 135,902 m in DoDs obtained from not co-registered and co-registered DTMs. The volume of debris flows measured at the catchment outlet during the same time interval amounts to 169,660 m. The comparison with debris-flow volume measures at the monitoring station shows, therefore, that the DTMs obtained from the co-registration processes generate more reliable DoDs than those obtained from the raw DTMs (without the alignment).

1.AbstractThe registration or alignment of diffusion weighted images (DWI) with other imaging modalities is a critical step in neuroimaging analysis. Within-subject T1-DWI co-registration is particularly instrumental. DWI-derived scalar images are commonly used as intermediates for T1-DWI co-registration, and the resulting registration transforms are applied to all other scalar images for analysis. The ideal registration intermediate should register well to T1 and other multimodal images and be practically easy to obtain. It is however, currently unclear which DWI-derived scalar image serves as the best intermediate. We aim to determine the best, practical, intermediate for image co-registration. T1 and DWI images were acquired from 20 healthy subjects. DWIs were acquired with 60 directions. Six DWI-derived scalar images were compared including: 1) fractional anisotropy (FA); 2) generalized FA (GFA); 3) B0 images; 4) mean DWIs with the B0 image (MDWI); 5) anisotropic power (AP) images. AP showed the smallest variability in registration improvements across all the tested DWI derived scalar images, and show the highest average percent changes with CC registration cost function (CC=1.2%, MI=15%). In contrast, the FA and GFA transforms resulted in significantly poorer registration across DWI types. The AP image was the DWI-derived scalar image that provided the most consistent registration to all other images. Practically, it is generated easily and so could be implemented in basic and clinical research pipelines currently using other intermediates. Given these findings, it is recommended that AP images be used for T1–DWI co-registration, and that FA and GFA images in particular be avoided.

PURPOSE Presurgical fMRI is an important tool for surgery navigation in achieving maximum resection of a brain tumor. However, the functional localization accuracy may be compromised by spatial transformation from echo-planar images to high-resolution structural images. We evaluated functional localization errors associated with the spatial transformation process using three algorithms commonly applied to the presurgical fMRI in the clinic. METHODS MR images of 20 brain tumor patients for presurgical evaluation of eloquent areas near motor cortices were analyzed. All fMRI data were spatially transferred to 3D T1-weighted images using three algorithms: (a) coordinate matching (CM), (b) automated registration (AR), and (c) AR plus manual adjustment (ARadj ). Activation clusters overlaid on original echo-planar images were manually delineated on slice-matched 2D T1- weighted images and then transferred to the 3D T1-weighted image volume, and served as the reference localization. Functional localization errors were estimated by measuring the distance between the reference localization and the activation cluster after spatial transformation and then compared for the three algorithms. RESULTS The 3D Euclidean distance for AR (10.2 ± 4.9 mm) was found to be significantly larger (P < 0.05) than those for CM (5.6 ± 2.6 mm) and ARadj (5.8 ± 3.0 mm) algorithms. The difference between the localization errors in CM and ARadj was not statistically significant. CONCLUSIONS A procedure was proposed to evaluate functional localization errors associated with spatial transformation in presurgical fMRI. Our results highlighted the necessity of routine quality control for the AR processing in the clinic.

To investigate the clinical usefulness and practicality of co-registration of Cone Beam CT (CBCT) with preoperative Magnetic Resonance Imaging (MRI) for intracochlear localization of electrodes after cochlear implantation.Images of 20 adult patients who underwent CBCT after implantation were co-registered with preoperative MRI scans. Time taken for co-registration was recorded. The images were analysed by clinicians of varying levels of expertise to determine electrode position and ease of interpretation.After a short learning curve, the average co-registration time was 10.78 minutes (StdDev 2.37). All clinicians found the co-registered images easier to interpret than CBCT alone. The mean concordance of CBCT vs. co-registered image analysis between consultant otologists was 60% (17-100%) and 86% (60-100%), respectively. The sensitivity and specificity for CBCT to identify Scala Vestibuli insertion or translocation was 100 and 75%, respectively. The negative predictive value was 100%.CBCT should be performed following adult cochlear implantation for audit and quality control of surgical technique. If SV insertion or translocation is suspected, co-registration with preoperative MRI should be performed to enable easier analysis. There will be a learning curve for this process in terms of both the co-registration and the interpretation of images by clinicians.

With more than 4 TB of data acquired every day, the Sentinel 2 mission poses new challenges for quality control (QC). To support the QC operations of Sentinel 2, a dedicated tool has been developed for improved efficiency and traceability of analyses. This tool aims at helping visual inspection by human operators through automatic product retrieval, generation of quicklook images and production of quality indicators. The article describes the product sampling strategy used to select products suitable for quality control checks. Then we present the methodology used to generate quicklooks, compute relative and multi-spectral co-registration performance. The final step is the production of end-to-end service performance indicators. Lessons learnt from the first year of operation of this tool are presented regarding detected product anomalies and measured performance trends.

Radiomics holds great promise in the field of cancer management. However, the clinical application of radiomics has been hampered by uncertainty about the robustness of the features extracted from the images. Previous studies have reported that radiomics features are sensitive to changes in voxel size resampling and interpolation, image perturbation, or slice thickness. This study aims to observe the variability of positron emission tomography (PET) radiomics features under the impact of co-registration with magnetic resonance imaging (MRI) using the difference percentage coefficient, and the Spearman’s correlation coefficient for three groups of images: (i) original PET, (ii) PET after co-registration with T1-weighted MRI and (iii) PET after co-registration with FLAIR MRI. Specifically, seventeen patients with brain cancers undergoing [11C]-Methionine PET were considered. Successively, PET images were co-registered with MRI sequences and 107 features were extracted for each mentioned group of images. The variability analysis revealed that shape features, first-order features and two subgroups of higher-order features possessed a good robustness, unlike the remaining groups of features, which showed large differences in the difference percentage coefficient. Furthermore, using the Spearman’s correlation coefficient, approximately 40% of the selected features differed from the three mentioned groups of images. This is an important consideration for users conducting radiomics studies with image co-registration constraints to avoid errors in cancer diagnosis, prognosis, and clinical outcome prediction.

Planar scintigraphy with 99mTc-pertechnetate or Meckel scan is the gold standard in the diagnosis of a bleeding Meckel’s diverticulum (MD) for pediatrics. However, several setbacks may occur during the interpretation of a scintigram, especially in cases of an atypical MD presentation. In this report, we highlight the importance of functional and anatomical image co-registration using a hybrid SPECT/CT scanner to precisely localize a MD lesion. An 18-month-old boy presented with severe hematochezia over 4 days with declining hemoglobin levels. He underwent a conventional 60-min dynamic planar imaging of the Meckel scan. Upon review of the Meckel scan, a suspicious increase in the 99mTc-pertechnetate uptake was observed at the right upper quadrant of the abdomen. Due to its atypical location at the right kidney, we could not differentiate between a physiological uptake of the right kidney or an ectopic gastric mucosa. The patient was imaged again using single-photon emission computed tomography (SPECT) and low-dose CT protocol with a hybrid SPECT/CT scanner, and the co-registration of both SPECT and CT images was able to confirm the MD, which was located anterior to the right kidney at the right hepatic flexure region. An exploratory laparotomy was then ensued to remove the bleeding MD. The patient was discharged after 3 days with no complications. In summary, this case illustrates that hybrid imaging modality and co-registration allow for a more definitive diagnosis, as well as a more precise localization of MD.

Introduction: Studies using functional connectivity and network analyses based on magnetoencephalography (MEG) with source localization are rapidly emerging in neuroscientific literature. However, these analyses currently depend on the availability of costly and sometimes burdensome individual MR scans for co-registration. We evaluated the consistency of these measures when using a template MRI, instead of native MRI, for the analysis of functional connectivity and network topology. Methods: Seventeen healthy participants underwent resting-state eyes-closed MEG and anatomical MRI. These data were projected into source space using an atlas-based peak voxel and a centroid beamforming approach either using (1) participants’ native MRIs or (2) the Montreal Neurological Institute's template. For both methods, time series were reconstructed from 78 cortical atlas regions. Relative power was determined in six classical frequency bands per region and globally averaged. Functional connectivity (phase lag index) between each pair of regions was calculated. The adjacency matrices were then used to reconstruct functional networks, of which regional and global metrics were determined. Intraclass correlation coefficients were calculated and Bland–Altman plots were made to quantify the consistency and potential bias of the use of template versus native MRI. Results: Co-registration with the template yielded largely consistent relative power, connectivity, and network estimates compared to native MRI. Discussion: These findings indicate that there is no (systematic) bias or inconsistency between template and native MRI co-registration of MEG. They open up possibilities for retrospective and prospective analyses to MEG datasets in the general population that have no native MRIs available. Hum Brain Mapp, 2017.

Covert shifts of attention that follow the presentation of a cue are associated with lateralized components in the event-related potential (ERP): the "early directing attention negativity" (EDAN) and the "anterior directing attention negativity" (ADAN). Traditionally, these shifts are thought to take place while gaze is fixated and, thus, in the absence of saccades. However, microsaccades of small amplitude (1°) occur frequently and involuntarily also during fixation and are closely correlated with spatial attention. To investigate potential links between microsaccades and lateralized ERP components, we simultaneously recorded eye movements and ERPs in a spatial cueing task. As a first major result, we show that both the posterior EDAN and the orientation of microsaccades align more strongly with the location of the task-relevant part of the cue stimulus than with the direction of the attention shift indicated by that cue. A coupling between microsaccades and EDAN was also present on the single-trial level: The EDAN was largest when microsaccades were oriented toward the relevant cue, but absent when microsaccades were oriented away from it, suggesting that EDAN and microsaccades are generated by the same neural network, which selects relevant stimuli and orients behavior toward them. As a second major result, we show that small corneoretinal artifacts from microsaccades, which fall below conventional EOG rejection thresholds, contaminate the measurement of the ADAN. After correcting the EEG for microsaccade-related artifacts with an optimized variant of independent component analysis, ADAN was abolished at frontal sites, but a genuine ADAN was still present at central sites. Thus, the combined measurement of microsaccades and lateralized ERPs sheds new light onto cue-elicited shifts of covert attention.

A framework for co-registering multi-temporal 3D point cloud surfaces (PCSs) is presented, which addresses the co-registration of urban and non-urban 3D surfaces formed by 3D points. These surfaces are acquired from different surface measurement sensors and are in different coordinate systems. No prior information about initial transformation parameters or proximate matching is assumed. A keypoint matching approach is proposed to co-register two PCSs. First, surface curvature information is utilized for scale-invariant keypoint extraction. Then, every keypoint is characterized by a scale, rotation, and translation invariant surface descriptor called the radial geodesic distance-slope histogram. Keypoints with similar surface descriptors on the two PCSs are matched using bipartite graph matching. Given scale, rotation and translation changes between PCS pairs, co-registration tests on multi-sensor urban and non-urban datasets gave rotation errors from 0.017° to 0.023°, translation errors from 0.007 m to 0.013 m and scale factor errors from 0.0002 to 0.0014.

Building detection in very high resolution (VHR) images is crucial for mapping and analysing urban environments. Since buildings are elevated objects, elevation data need to be integrated with images for reliable detection. This process requires two critical steps: optical-elevation data co-registration and aboveground elevation calculation. These two steps are still challenging to some extent. Therefore, this paper introduces optical-elevation data co-registration and normalization techniques for generating a dataset that facilitates elevation-based building detection. For achieving accurate co-registration, a dense set of stereo-based elevations is generated and co-registered to their relevant image based on their corresponding image locations. To normalize these co-registered elevations, the bare-earth elevations are detected based on classification information of some terrain-level features after achieving the image co-registration. The developed method was executed and validated. After implementation, 80% overall-quality of detection result was achieved with 94% correct detection. Together, the developed techniques successfully facilitate the incorporation of stereo-based elevations for detecting buildings in VHR remote sensing images.