Scanner Calibration Research Articles

Numerical Simulations for Calibration Setup for Dynamic Contrast-Enhanced Ultrasonography Imaging Protocol.

This study presents an investigation of an innovative microfluidic flow separator using both numerical and experimental approaches to calibrate contrast-enhanced ultrasound scanners. Numerical simulations were conducted using Lagrangian particles tracking and passive scalar transport methodologies using the OpenFOAM software. The experimental validation confirmed the accuracy of the numerical simulations, particularly at an imposed total pressure of , showing an excellent agreement in particle distributions. The study emphasizes the computational efficiency and modeling of passive scalar transport, providing valuable understanding into the behavior of scalar quantities in microfluidic systems. An optimized diffusion coefficient value of was identified, showing its critical role in achieving accurate simulation results and optimizing the performance of microfluidic flow separators for contrast-enhanced ultrasound scanner calibration.

Reliability of Accuracy-Based Calibration in Quantifying Systematic Errors of Static LiDAR

The calibration of terrestrial laser scanners (TLSs) is crucial for ensuring high-quality 3D data. While system calibration often relies on precision-based methods without reference points, this study explores accuracy-based approaches incorporating reference values. TLS self-calibration was performed using point-based and line-based constraints with reference points established through close-range photogrammetry (CRP). The evaluation assessed calibration parameters (CPs), standard deviation, residuals, and correlation coefficient. Results show that the line-based approach improved accuracy by up to 60%, whereas the point-based method exhibited significant deviations. Consequently, while accuracy-based approaches can enhance TLS self-calibration, the line-based constraint is notably more effective.

129Xe Image Processing Pipeline: An open-source, graphical user interface application for the analysis of hyperpolarized 129Xe MRI.

Hyperpolarized 129Xe MRI presents opportunities to assess regional pulmonary microstructure and function. Ongoing advancements in hardware, sequences, and image processing have helped it become increasingly adopted for both research and clinical use. As the number of applications and users increase, standardization becomes crucial. To that end, this study developed an executable, open-source 129Xe image processing pipeline (XIPline) to provide a user-friendly, graphical user interface-based analysis pipeline to analyze and visualize 129Xe MR data, including scanner calibration, ventilation, diffusion-weighted, and gas exchange images. The customizable XIPline is designed in MATLAB to analyze data from all three major scanner platforms. Calibration data is processed to calculate optimal flip angle and determine129Xe frequency offset. Data processing includes loading, reconstructing, registering, segmenting, and post-processing images. Ventilation analysis incorporates three common algorithms to calculate ventilation defect percentage and novel techniques to assess defect distribution and ventilation texture. Diffusion analysis features ADC mapping, modified linear binning to account for ADC age-dependence, and common diffusion morphometry methods. Gas exchange processing uses a generalized linear binning for data acquired using 1-point Dixon imaging. The XIPline workflow is demonstrated using analysis from representative calibration, ventilation, diffusion, and gas exchange data. The application will reduce redundant effort when implementing new techniques across research sites by providing an open-source framework for developers. In its current form, it offers a robust and adaptable platform for 129Xe MRI analysis to ensure methodological consistency, transparency, and support for collaborative research across multiple sites and MRI manufacturers.

Two-parametric prescan calibration of gradient-induced sampling errors for rosette MRI.

The aim of this study was to develop a simple, robust, and easy-to-use calibration procedure for correcting misalignments in rosette MRI k-space sampling, with the objective of producing images with minimal artifacts. Quick automatic calibration scans were proposed for the beginning of the measurement to collect information on the time course of the rosette acquisition trajectory. A two-parameter model was devised to match the measured time-varying readout gradient delays and approximate the actual rosette sampling trajectory. The proposed calibration approach was implemented, and performance assessment was conducted on both phantoms and human subjects. The fidelity of phantom and in vivo images exhibited significant improvement compared with uncorrected rosette data. The two-parameter calibration approach also demonstrated enhanced precision and reliability, as evidenced by quantitative relaxometry analyses. Adequate correction of data sampling is a crucial step in rosette MRI. The presented experimental results underscore the robustness, ease of implementation, and suitability for routine experimental use of the proposed two-parameter rosette trajectory calibration approach.

ALMACAL

The ALMACAL survey is based on a database of reprocessed ALMA calibration scans suitable for scientific analysis, observed as part of regular PI observations. We present all the data accumulated from the start of ALMA operations until May 2022 for 1047 calibrator fields across the southern sky spanning ALMA Bands 3 to 10 (∼84 − 950 GHz), so-called ALMACAL−22. Encompassing over 1000 square arcmin and accumulating over 2000 hours of integration time, ALMACAL is not only one of the largest ALMA surveys to date, but it continues to grow with each new scientific observation. We outline the methods for processing and imaging a subset of the highest-quality data (‘pruned sample’). Using deconvolution techniques within the visibility data (uv plane), we created data cubes as the final product for further scientific analysis. We describe the properties and shortcomings of ALMACAL and compare its area and sensitivity with other sub-millimetre surveys. Notably, ALMACAL overcomes limitations of previous sub-millimetre surveys, such as small sky coverage and the effects of cosmic variance. Moreover, we discuss the improvements introduced by the latest version of this dataset that will enhance our understanding of dusty star-forming galaxies, extragalactic absorption lines, active galactic nucleus physics, and ultimately the evolution of molecular gas.

External parameter calibration of laser scanner based on the combination of plane-control-based and plane-constraints-based methods

Accurate calibration of the external parameters of a laser scanner is crucial to ensure consistency in data representation from multiple sources. Plane features, known for their simplicity and ease of extraction, are widely used in external parameter calibration. The use of control planes with known plane parameters enables the simultaneous estimation of both translation and rotation parameters, while the use of planes with unknown parameters allows for efficient self-calibration. In this paper, we introduce a novel method that combines the strengths of both types of plane calibration methods to calibrate the external parameters of a laser scanner. The approach, with the help of a Gauss-Helmert adjustment model, integrates control and constraint planes to calibrate the external parameters. The method boasts the ease and accessibility offered by the plane constraint method, utilizing fewer control features while successfully estimating the external parameters of the laser scanner. To evaluate the feasibility of this method, two sets of 12 calibration experiments were conducted on the mobile measurement system platform. Notably, the residual Root Mean Square Errors (RMSE) obtained from these experiments were comparable to those achieved using traditional plane-control-based method. Furthermore, the external parameter correlation aligns with that obtained using the plane-control-based method, while the plane parameter correlation exhibits similarity to that obtained using the plane-constraint-based method. These results confirm that our method effectively minimizes the requirement for control features and enables more convenient calibration of the external parameters of the laser scanner.

Additive Manufacturing of Ceramic Reference Spheres by Stereolithography (SLA)

Additive Manufacturing (AM) is advancing technologically towards the production of components for high-demand mechanical applications with stringent dimensional accuracy, leveraging metallic and ceramic raw materials. The AM process for ceramic components, known as Ultraviolet Laser Stereolithography (SLA), enables the fabrication of unique parts or small batches without substantial investments in molds and dies, and avoids the problems associated with traditional manufacturing, which involves multiple stages and final machining for precision. This study addresses the need to produce reference elements or targets for metrological applications, including verification, adjustment, or calibration of 3D scanners and mid- to high-range optical sensors. Precision spheres are a primary geometry in this context due to their straightforward mathematical definition, facilitating rapid and accurate error detection in equipment. Our objective is to exploit this novel SLA process along with the advantageous optical properties of technical ceramics (such as being white, matte, lightweight, and corrosion-resistant) to materialize these reference objects. Specifically, this work involves the fabrication of alumina hemispheres using SLA. The manufacturing process incorporates four design variables (wall thickness, support shape, fill type, and orientation) and one manufacturing variable (the arrangement of spheres on the printing tray). To evaluate the impact of the design variables, dimensional and geometric parameters (GD&T), including diameters, form errors, and their distribution on the surface of the sphere, have been characterized. These measurements are conducted with high accuracy using a Coordinate Measuring Machine (CMM). The study also examines the influence of these variables in the dimensional and geometric accuracy of the spheres. Correlations between various parameters were identified, specifically highlighting critical factors affecting process precision, such as the position of the piece on the print tray and the wall thickness value. The smallest diameter errors were recorded at the outermost positions of the tray (rear and front), while the smallest shape errors were found at the central position, in both cases with errors in the range of tens of micrometers. In any case, the smallest deformations were observed with the highest wall thickness (2 mm).

Adaptive remanufacturing for freeform surface parts based on linear laser scanner and robotic laser cladding

Freeform surface parts play a significant role in the aerospace industry, the mold- manufacturing industry and the automobile industry, and it is energy-saving, material-saving, time-saving and environmentally beneficial to remanufacture the damaged components to restore their functionality and performance. Due to the complex geometry of the freeform surface wear, the adaptive remanufacturing of freeform surface parts is confronted with challenges. In this paper, an adaptive remanufacturing method for freeform surface parts based on linear laser scanner and robotic laser cladding is proposed to realize the precise freeform surface measurement and optimized remanufacturing path generation. On the one hand, a systematic wear measurement and assessment method is proposed to precisely locate and quantify the wear. With the noncontact calibration of the laser scanner and industrial robot, the contour of the target surface is real-timely measured and the reverse model is efficiently constructed, which provides detailed 3D morphological information of the worn freeform surface for the latter wear analysis. Next, considering the considerable difference between the reverse model and the nominal model, a refined model aligning method weighted by surface wear segmentation is proposed to minimize the alignment error and, further, the difference entity to be additively manufactured is obtained by discrete model comparison. On the other hand, to cope with the unsatisfactory binding strength over the freeform surface basis and small fragments of the working path for the traditional plane or cylinder slicing method, a novel remanufacturing path generation method is proposed. Considering the curvature distribution of the freeform surface, an optimized equidistant freeform surface slicing method is especially proposed for the difference entity to realize the adaptive fitting to the freeform basin. Furthermore, based on the equivalent volume overlapping model of laser cladding, the cladding track filling method for the freeform surface slicing is designed with the optimized track-to-track distance, which can reduce surface waviness and improve remanufacturing efficiency. Finally, simulations and experiments for the remanufacturing scenario of the steam turbine blade are conducted to verify the validity and feasibility of the proposed adaptive remanufacturing method for freeform surface parts based on linear laser scanner and robotic laser cladding.

Unfolding coil localized errors from an imperfect slice profile using a structured autocalibration matrix: An application to reduce outflow effects in cine bSSFP imaging.

Balanced steady-state free precession (bSSFP) imaging is susceptible to outflow effects where excited spins leaving the slice as part of the blood stream are misprojected back onto the imaging plane. Previous work proposed using slice-encoding steps to localize these outflow effects from corrupting the target slice, at the expense of prolonged scan time. This present study extends this idea by proposing a means of significantly reducing most of the outflowing signal from the imaged slice using a coil localization method that acquires a slice-encoded calibration scan in addition to the 2D data, without being nearly as time-demanding as our previous method. This coil localization method is titled UNfolding Coil Localized Errors from an imperfect slice profile using a Structured Autocalibration Matrix (UNCLE SAM). Retrospective and prospective evaluations were carried out. Both featured a 2D acquisition and a separate slice-encoded calibration of the center in-plane -space lines across all desired slice-encoding steps. Retrospective results featured a slice-by-slice comparison of the slice-encoded images with UNCLE SAM. UNCLE SAM's subtraction from the slice-encoded image was compared with a subtraction from the flow-corrupted 2D image, to demonstrate UNCLE SAM's capability to unfold outflowing spins. UNCLE SAM's comparison with slice encoding showed that UNCLE SAM was able to unfold up to 74% of what slice encoding achieved. Prospective results showed significant reduction in outflow effects with only a marginal increase in scan time from the 2D acquisition. We developed a method that effectively unfolds most outflowing spins from corrupting the target slice and does not require the explicit use of slice-encoding gradients. This development offers a method to reduce most outflow effects from the target slice within a clinically feasible scan duration compared with the fully sampled slice-encoding technique.

Design and Validation of a Patient-Specific Stereotactic Frame for Transcranial Ultrasound Therapy.

Transcranial-focused ultrasound (tFUS) procedures such as neuromodulation and blood-brain barrier (BBB) opening require precise focus placement within the brain. MRI is currently the most reliable tool for focus localization but can be prohibitive for procedures requiring recurrent therapies. We designed, fabricated, and characterized a patient-specific, 3-D-printed, stereotactic frame for repeated tFUS therapy. The frame is compact, with minimal footprint, can be removed and re-secured between treatments while maintaining sub-mm accuracy, and will allow for precise and repeatable transcranial FUS treatment without the need for MR-guidance following the initial calibration scan. Focus localization and repeatability were assessed via MR-thermometry and MR-acoustic radiation force imaging (ARFI) on an ex vivo skull phantom and in vivo nonhuman primates (NHPs), respectively. Focal localization, registration, steering, and re-steering were accomplished during the initial MRI calibration scan session. Keeping steering coordinates fixed in subsequent therapy and imaging sessions, we found good agreement between steered foci and the intended target, with target registration error (TRE) of 1.2 ± 0.3 ( n = 4 , ex vivo) and 1.0 ± 0.5 ( n = 3 , in vivo) mm. Focus position (steered and non-steered) was consistent, with sub-mm variation in each dimension between studies. Our 3-D-printed, patient-specific stereotactic frame can reliably position and orient the ultrasound transducer for repeated targeting of brain regions using a single MR-based calibration. The compact frame allows for high-precision tFUS to be carried out outside the magnet and could help reduce the cost of tFUS treatments where repeated application of an ultrasound focus is required with high precision.

Asynchronous calibration of a CT scanner for bone mineral density estimation: sources of error and correction.

The estimation of BMD with CT scans requires a calibration method, usually based on a phantom. In asynchronous calibration, the phantom is scanned separately from the patient. A standardized acquisition protocol must be used to avoid variations between patient and phantom. However, variations can still be induced, for example, by temporal fluctuations or patient characteristics. Based on the further use of 739 forensic and 111 clinical CT scans, this study uses the proximal femur BMD value ("total hip") to assess asynchronous calibration accuracy, using in-scan calibration as ground truth. It identifies the parameters affecting the calibration accuracy and quantifies their impact. For time interval and table height, the impact was measured by calibrating the CT scan twice (once using the phantom scan with closest acquisition parameters and once using a phantom scan with standard values) and comparing the calibration accuracy. For other parameters such as body weight, the impact was measured by computing a linear regression between parameter values and calibration accuracy. Finally, this study proposes correction methods to reduce the effect of these parameters and improve the calibration accuracy. The BMD error of the asynchronous calibration, using the phantom scan with the closest acquisition parameters, was -1.2 ± 1.7% for the forensic and - 1.6 ± 3.5% for the clinical dataset. Among the parameters studied, time interval and body weight were identified as the main sources of error for asynchronous calibration, followed by table height and reconstruction kernel. Based on these results, a correction method was proposed to improve the calibration accuracy.

Fast and reliable quantitative measures of white matter development with magnetic resonance fingerprinting.

Developmental cognitive neuroscience aims to shed light on evolving relationships between brain structure and cognitive development. To this end, quantitative methods that reliably measure individual differences in brain tissue properties are fundamental. Standard qualitative MRI sequences are influenced by scan parameters and hardware-related biases, and also lack physical units, making the analysis of individual differences problematic. In contrast, quantitative MRI can measure physical properties of the tissue but with the cost of long scan durations and sensitivity to motion. This poses a critical limitation for studying young children. Here, we examine the reliability and validity of an efficient quantitative multiparameter mapping method - Magnetic Resonance Fingerprinting (MRF) - in children scanned longitudinally. We focus on T1 values in white matter, since quantitative T1 values are known to primarily reflect myelin content, a key factor in brain development. Forty-nine children aged 8-13y (mean 10.3y ±1.4) completed two scanning sessions 2-4 months apart. In each session, two 2-minute 3D-MRF scans at 1mm isotropic resolution were collected to evaluate the effect of scan duration on image quality and scan-rescan reliability. A separate calibration scan was used to measure B0 inhomogeneity and correct for bias. We examined the impact of scan time and B0 inhomogeneity correction on scan-rescan reliability of values in white matter, by comparing single 2-min and combined two 2-min scans, with and without B0-correction. Whole-brain voxel-based reliability analysis showed that combining two 2-min MRF scans improved reliability (pearson's r=0.87) compared with a single 2-min scan (r=0.84), while B0-correction had no effect on reliability in white matter (r=0.86 and 0.83 4-min vs 2-min). Using diffusion tractography, we delineated MRF-derived T1 profiles along major white matter fiber tracts and found similar or higher reliability for T1 from MRF compared to diffusion parameters (based on a 10-minute dMRI scan). Lastly, we found that T1 values in multiple white matter tracts were significantly correlated with age. In sum, MRF-derived T1 values were highly reliable in a longitudinal sample of children and replicated known age effects. Reliability in white matter was improved by longer scan duration but was not affected by B0-correction, making it a quick and straightforward scan to collect. We propose that MRF provides a promising avenue for acquiring quantitative brain metrics in children and patient populations where scan time and motion are of particular concern.

Quality control of quantitative diffusion-weighted magnetic resonance imaging: metrological problems

Quantitative magnetic resonance imaging is a modern method for detecting pathological changes in the patient’s tissues. However, images with quantitative characteristics are not widely used due to the limitation of the accuracy and reproducibility of the measured values. The purpose of this work is to formulate the metrological problem of quantitative magnetic resonance imaging and to ensure the reliability of research based on the analysis of practical approaches to quality control of diffusion-weighted magnetic resonance imaging. As part of the work performed, an analysis was carried out of the use of phantoms as means to ensure quality control of certain parameters of quantitative magnetic resonance imaging. The importance of validation was noted, the metrics used to control the quality of quantitative magnetic resonance imaging were highlighted, an overview of examples of clinical studies using diffusion-weighted magnetic resonance imaging was presented. It was found that accurate calibration and testing of magnetic resonance imaging scanners, as well as verification of image analysis tools, are necessary for the use of quantitative magnetic resonance imaging data in clinical practice.

Scan-Specific Self-Supervised Bayesian Deep Non-Linear Inversion for Undersampled MRI Reconstruction.

Magnetic resonance imaging is subject to slow acquisition times due to the inherent limitations in data sampling. Recently, supervised deep learning has emerged as a promising technique for reconstructing sub-sampled MRI. However, supervised deep learning requires a large dataset of fully-sampled data. Although unsupervised or self-supervised deep learning methods have emerged to address the limitations of supervised deep learning approaches, they still require a database of images. In contrast, scan-specific deep learning methods learn and reconstruct using only the sub-sampled data from a single scan. Here, we introduce Scan-Specific Self-Supervised Bayesian Deep Non-Linear Inversion (DNLINV) that does not require an auto calibration scan region. DNLINV utilizes a Deep Image Prior-type generative modeling approach and relies on approximate Bayesian inference to regularize the deep convolutional neural network. We demonstrate our approach on several anatomies, contrasts, and sampling patterns and show improved performance over existing approaches in scan-specific calibrationless parallel imaging and compressed sensing.

Imaging plate scanners calibration and the attenuation behavior of imaging plate signals

Abstract Based on previously reported work, we propose a new method for calibrating image plate (IP) scanners, offering greater flexibility and convenience, which can be extended to the calibration tasks of various scanner models. This method was applied to calibrate the sensitivity of a GE Typhoon FLA 7000 scanner. Additionally, we performed a calibration of the spontaneous signal attenuation behavior for BAS-MS, BAS-SR, and BAS-TR type IPs under the 20±1 °C environmental conditions, and observed significant signal carrier diffusion behavior in BAS-MS IP. The calibration results lay a foundation for further research on the interaction between ultra-short, ultra-intense lasers and matter.

Shape functions to scanner comparison

In the optical scanning, the processed data are in the form of point clouds that can be organised into the triangular meshes and can represent the surface with the given inaccuracy of the scanner. Meshes of special surfaces (such as sphere or ball bar) are used for the scanner calibration, qualification and verification. These artefacts restrict the calibration process, because their sizes must be periodically calibrated by the relevant institutions.The aim of this paper is to present new possibilities for optical laser scanner accuracy comparison. Three types of laser scanners with different accuracies were used. The calibration sphere was used to compare the results of the deviations (the commonly used method for scanner accuracy verification) from calibrated value with the results of new methods that use shape functions measuring distances, cone heights or curvatures. The measurement system analysis was used to verify that these functions can be used for scanners comparison. The comparison of shape distributions obtained from results of shape functions in the form of polylines was used to compare scanners according to their accuracies. The comparison of shape distribution results was done using ranges and Minkowski L1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${L}_{1}$$\\end{document} norm.

Nonlinear Gradient Field Estimation in Diffusion MRI Tensor Simulation.

Gradient nonlinearities not only induce spatial distortion in magnetic resonance imaging (MRI), but also introduce discrepancies between intended and acquired diffusion sensitization in diffusion weighted (DW) MRI. Advances in scanner performance have increased the importance of correcting gradient nonlinearities. The most common approaches for gradient nonlinear field estimations rely on phantom calibration field maps which are not always feasible, especially on retrospective data. Here, we derive a quadratic minimization problem for the complete gradient nonlinear field (L(r)). This approach starts with corrupt diffusion signal and estimates the L(r) in two scenarios: (1) the true diffusion tensor known and (2) the true diffusion tensor unknown (i.e., diffusion tensor is estimated). We show the validity of this mathematical approach, both theoretically and through tensor simulation. The estimated field is assessed through diffusion tensor metrics: mean diffusivity (MD), fractional anisotropy (FA), and principal eigenvector (V1). In simulation with 300 diffusion tensors, the study shows the mathematical model is not ill-posed and remains stable. We find when the true diffusion tensor is known (1) the change in determinant of the estimated L(r) field and the true field is near zero and (2) the median difference in estimated L(r) corrected diffusion metrics to true values is near zero. We find the results of L(r) estimation are dependent on the level of L(r) corruption. This work provides an approach to estimate gradient field without the need for additional calibration scans. To the best of our knowledge, the mathematical derivation presented here is novel.

Intra-scan RF power amplifier drift correction.

The drift in radiofrequency (RF) power amplifiers (RFPAs) is assessed and several contributing factors are investigated. Two approaches for prospective correction of drift are proposed and their effectiveness is evaluated. RFPA drift assessment encompasses both intra-pulse and inter-pulse drift analyses. Scan protocols with varying flip angle (FA), RF length, and pulse repetition time (TR) are used to gauge the influence of these parameters on drift. Directional couplers (DICOs) monitor the forward waveforms of the RFPA outputs. DICOs data is stored for evaluation, allowing calculation of correction factors to adjust RFPAs' transmit voltage. Two correction methods, predictive and run-time, are employed: predictive correction necessitates a calibration scan, while run-time correction calculates factors during the ongoing scan. RFPA drift is indeed influenced by the RF duty-cycle, and in the cases examined with a maximum duty-cycle of 66%, the potential drift is approximately 41% or 15%, depending on the specific RFPA revision. Notably, in low transmit voltage scenarios, FA has minimal impact on RFPA drift. The application of predictive and run-time drift correction techniques effectively reduces the average drift from 10.0% to less than 1%, resulting in enhanced MR signal stability. Utilizing DICO recordings and implementing a feedback mechanism enable the prospective correction of RFPA drift. Having a calibration scan, predictive correction can be utilized with fewer complexity; for enhanced performance, a run-time approach can be employed.

Material decomposition maps based calibration of dual energy CT scanners for proton therapy planning: a phantom study

We introduce a new calibration method for dual energy CT (DECT) based on material decomposition (MD) maps, specifically iodine and water MD maps. The aim of this method is to provide the first DECT calibration based on MD maps. The experiments were carried out using a general electric (GE) revolution CT scanner with ultra-fast kV switching and used a density phantom by GAMMEX for calibration and evaluation. The calibration process involves several steps. First, we tested the ability of MD values to reproduce Hounsfield unit (HU) values of single energy CT (SECT) acquisitions and it was found that the errors were below 1%, validating their use for HU reproduction. Next, the different definitions of computed Z values were compared and the robustness of the approach based on the materials’ composition was confirmed. Finally, the calibration method was compared with a previous method by Bourque et al, providing a similar level of accuracy and superior performance in terms of precision. Overall, this novel DECT calibration method offers improved accuracy and reliability in determining tissue-specific physical properties. The resulting maps can be valuable for proton therapy treatments, where precise dose calculations and accurate tissue differentiation are crucial for optimal treatment planning and delivery.

Licking the plate: Dusty star-forming galaxies buried in the ALMA calibration data

Deep, unbiased surveys are essential to decipher the cosmic evolution of galaxies. The submillimetre (submm) and millimetre (mm) windows complement the UV/optical waveband and are key to revealing the cold and dusty Universe. Traditional ways of conducting deep surveys resort to either lensed fields or target small areas for ultra-long integrations. These surveys have greatly advanced our understanding of dusty star-forming galaxies (DSFGs), but are susceptible to lensing uncertainties and cosmic variance and will be expensive to expand. Here, we summarise our recent multi-wavelength survey of DSFGs in the vicinity of ALMA’s calibrators: the ALMACAL survey. These fields have accumulated many hundreds of hours of on-source time, reaching depths and effective areas that are competitive with bespoke cosmological surveys. We summarise the multi-wavelength number counts from ALMACAL and the resolved fraction of the Cosmic Infrared Background (CIB) from submm to mm wave-lengths. Meanwhile, combining all available ALMA observations in each field results in impressive frequency coverage, which often yields the redshifts of these DSFGs. The ALMACAL survey has demonstrated the scientific value of calibration scans for all submm/mm and radio telescopes, existing and planned.