Loss Of Resolution Research Articles

An Ultra-Throughput Boost Method for Gamma-Ray Spectrometers

(1) Background: Generally, in nuclear medicine and nuclear power plants, energy spectrum measurements and radioactive nuclide identification are required for evaluation of strong radiation fields to ensure nuclear safety and security; thereby, damage is prevented to nuclear facilities caused by natural disasters or the criminal smuggling of nuclear materials. High count rates can lead to signal accumulation, negatively affecting the performance of gamma spectrometers, and in severe cases, even damaging the detectors. Higher pulse throughput with better energy resolution is the ultimate goal of a gamma-ray spectrometer. Traditionally, pileup pulses, which cause dead time and affect throughput, are rejected to maintain good energy resolution. (2) Method: In this paper, an ultra-throughput boost (UTB) off-line processing method was used to improve the throughput and reduce the pileup effect of the spectrometer. Firstly, by fitting the impulse signal of the detector, the response matrix was built by the functional model of a dual exponential tail convolved with the Gaussian kernel; then, a quadratic programming method based on a non-negative least squares (NNLS) algorithm was adopted to solve the constrained optimization problem for the inversion. (3) Results: Both the simulated and experimental results of the UTB method show that most of the impulses in the pulse sequence from the scintillator detector were restored to δ-like pulses, and the throughput of the UTB method for the NaI(Tl) spectrometer reached 207 kcps with a resolution of 7.71% @661.7 keV. A reduction was also seen in the high energy pileup phenomenon. (4) Conclusions: We conclude that the UTB method can restore individual and piled-up pulses to δ-like sequences, effectively boosting pulse throughput and suppressing high-energy tailing and sum peaks caused by the pileup effect at the cost of a slight loss in energy resolution.

UHead

The focus of Advanced driver-assistance systems (ADAS) is extending from the vehicle and road conditions to the driver because the driver's attention is critical to driving safety. Although existing sensor and camera based methods can monitor driver attention, they rely on specialised hardware and environmental conditions. In this paper, we aim to develop an effective and easy-to-use driver attention monitoring system based on UWB radar. We exploit the strong association between head motions and driver attention and propose UHead that infers driver attention by monitoring the direction and angle of the driver's head rotation. The core idea is to extract rotational time-frequency representation from reflected signals and to estimate head rotation angles from complex head reflections. To eliminate the dynamic noise generated by other body parts, UHead leverages the large magnitude and high velocity of head rotation to extract head motion information from the dynamically coupled information. UHead uses a bilinear joint time-frequency representation to avoid the loss of time and frequency resolution caused by windowing of traditional methods. We also design a head structure-based rotation angle estimation algorithm to accurately estimate the rotation angle from the time-varying rotation information of multiple reflection points in the head. Experimental results show that we achieve 12.96° median error of 3D head rotation angle estimation in real vehicle scenes.

Towards Learning Discrete Representations via Self-Supervision for Wearables-Based Human Activity Recognition.

Human activity recognition (HAR) in wearable and ubiquitous computing typically involves translating sensor readings into feature representations, either derived through dedicated pre-processing procedures or integrated into end-to-end learning approaches. Independent of their origin, for the vast majority of contemporary HAR methods and applications, those feature representations are typically continuous in nature. That has not always been the case. In the early days of HAR, discretization approaches had been explored-primarily motivated by the desire to minimize computational requirements on HAR, but also with a view on applications beyond mere activity classification, such as, for example, activity discovery, fingerprinting, or large-scale search. Those traditional discretization approaches, however, suffer from substantial loss in precision and resolution in the resulting data representations with detrimental effects on downstream analysis tasks. Times have changed, and in this paper, we propose a return to discretized representations. We adopt and apply recent advancements in vector quantization (VQ) to wearables applications, which enables us to directly learn a mapping between short spans of sensor data and a codebook of vectors, where the index comprises the discrete representation, resulting in recognition performance that is at least on par with their contemporary, continuous counterparts-often surpassing them. Therefore, this work presents a proof of concept for demonstrating how effective discrete representations can be derived, enabling applications beyond mere activity classification but also opening up the field to advanced tools for the analysis of symbolic sequences, as they are known, for example, from domains such as natural language processing. Based on an extensive experimental evaluation of a suite of wearable-based benchmark HAR tasks, we demonstrate the potential of our learned discretization scheme and discuss how discretized sensor data analysis can lead to substantial changes in HAR.

An Optical Frequency Domain Reflectometer's (OFDR) Performance Improvement via Empirical Mode Decomposition (EMD) and Frequency Filtration for Smart Sensing.

We describe a method for reducing the cost of optical frequency domain reflectometer (OFDR) hardware by replacing two reference channels, including an auxiliary interferometer and a gas cell, with a single channel. To extract useful information, digital signal processing methods were used: digital frequency filtering, as well as empirical mode decomposition. It is shown that the presented method helps to avoid the use of an unnecessary analog-to-digital converter and photodetector, while the OFDR trace is restored by the equal frequency resampling (EFR) algorithm without loss of high resolution and with good measurement repeatability.

Ultra-rapid, Free-breathing, Real-time Cardiac Cine MRI Using GRASP Amplified with View Sharing and KWIC Filtering.

Purpose To achieve ultra-high temporal resolution (approximately 20 msec) in free-breathing, real-time cardiac cine MRI using golden-angle radial sparse parallel (GRASP) reconstruction amplified with view sharing (VS) and k-space-weighted image contrast (KWIC) filtering. Materials and Methods Fourteen pediatric patients with congenital heart disease (mean age [SD], 9 years ± 2; 13 male) and 10 adult patients with arrhythmia (mean age, 62 years ± 8; nine male) who underwent both standard breath-hold cine and free-breathing real-time cine using GRASP were retrospectively identified. To achieve high temporal resolution, each time frame was reconstructed using six radial spokes, corresponding to acceleration factors ranging from 24 to 32. To compensate for loss in spatial resolution resulting from over-regularization in GRASP, VS and KWIC filtering were incorporated. The blur metric, visual image quality scores, and biventricular parameters were compared between clinical and real-time cine images. Results In pediatric patients, the incorporation of VS and KWIC into GRASP (ie, GRASP + VS + KWIC) produced significantly (P < .05) sharper x-y-t (blur metric: 0.36 ± 0.03, 0.41 ± 0.03, 0.48 ± 0.03, respectively) and x-y-f (blur metric: 0.28 ± 0.02, 0.31 ± 0.03, 0.37 ± 0.03, respectively) component images compared with GRASP + VS and conventional GRASP. Only the noise score differed significantly between GRASP + VS + KWIC and clinical cine; all visual scores were above the clinically acceptable (3.0) cutoff point. Biventricular volumetric parameters strongly correlated (R2 > 0.85) between clinical and real-time cine images reconstructed with GRASP + VS + KWIC and were in good agreement (relative error < 6% for all parameters). In adult patients, the visual scores of all categories were significantly lower (P < .05) for clinical cine compared with real-time cine with GRASP + VS + KWIC, except for noise (P = .08). Conclusion Incorporating VS and KWIC filtering into GRASP reconstruction enables ultra-high temporal resolution (approximately 20 msec) without significant loss in spatial resolution. Keywords: Cine, View Sharing, k-Space-weighted Image Contrast Filtering, Radial k-Space, Pediatrics, Arrhythmia, GRASP, Compressed Sensing, Real-Time, Free-Breathing Supplemental material is available for this article. © RSNA, 2024.

Super Resolution Dual-Energy Cone-Beam CT Imaging With Dual-Layer Flat-Panel Detector.

In flat-panel detector (FPD) based cone-beam computed tomography (CBCT) imaging, the native receptor array is usually binned into a smaller matrix size. By doing so, the signal readout speed could be increased by 4-9 times at the expense of a spatial resolution loss of 50%-67%. Clearly, such manipulation poses a key bottleneck in generating high spatial and high temporal resolution CBCT images at the same time. In addition, the conventional FPD is also difficult in generating dual-energy CBCT images. In this paper, we propose an innovative super resolution dual-energy CBCT imaging method, named as suRi, based on dual-layer FPD (DL-FPD) to overcome these aforementioned difficulties at once. With suRi, specifically, a 1D or 2D sub-pixel (half pixel in this study) shifted binning is applied instead of the conventionally aligned binning to double the spatial sampling rate during the dual-energy data acquisition. As a result, the suRi approach provides a new strategy to enable high spatial resolution CBCT imaging while at high readout speed. Moreover, a penalized likelihood material decomposition algorithm is developed to directly reconstruct the high resolution bases from these dual-energy CBCT projections containing sub-pixel shifts. Numerical and physical experiments are performed to validate this newly developed suRi method with phantoms and biological specimen. Results demonstrate that suRi can significantly improve the spatial resolution of the CBCT image. We believe this developed suRi method would greatly enhance the imaging performance of the DL-FPD based dual-energy CBCT systems in future.

Multivariate pattern analysis: a method and software to reveal, quantify, and visualize predictive association patterns in multicollinear data

BackgroundStrongly multicollinear covariates, such as those typically represented in metabolomics applications, represent a challenge for multivariate regression analysis. These challenges are commonly circumvented by reducing the number of covariates to a subset of linearly independent variables, but this strategy may lead to loss of resolution and thus produce models with poorer interpretative potential. The aim of this work was to implement and illustrate a method, multivariate pattern analysis (MVPA), which can handle multivariate covariates without compromising resolution or model quality.ResultsMVPA has been implemented in an open-source R package of the same name, mvpa. To facilitate the usage and interpretation of complex association patterns, mvpa has also been integrated into an R shiny app, mvpaShiny, which can be accessed on www.mvpashiny.org. MVPA utilizes a general projection algorithm that embraces a diversity of possible models. The method handles multicollinear and even linear dependent covariates. MVPA separates the variance in the data into orthogonal parts within the frame of a single joint model: one part describing the relations between covariates, outcome, and explanatory variables and another part describing the “net” predictive association pattern between outcome and explanatory variables. These patterns are visualized and interpreted in variance plots and plots for pattern analysis and ranking according to variable importance. Adjustment for a linear dependent covariate is performed in three steps. First, partial least squares regression with repeated Monte Carlo resampling is used to determine the number of predictive PLS components for a model relating the covariate to the outcome. Second, postprocessing of this PLS model by target projection provided a single component expressing the predictive association pattern between the outcome and the covariate. Third, the outcome and the explanatory variables were adjusted for the covariate by using the target score in the projection algorithm to obtain “net” data. We illustrate the main features of MVPA by investigating the partial mediation of a linearly dependent metabolomics descriptor on the association pattern between a measure of insulin resistance and lifestyle-related factors.ConclusionsOur method and implementation in R extend the range of possible analyses and visualizations that can be performed for complex multivariate data structures. The R packages are available on github.com/liningtonlab/mvpa and github.com/liningtonlab/mvpaShiny.

Unsupervised Domain-Adaptive SAR Ship Detection Based on Cross-Domain Feature Interaction and Data Contribution Balance

Due to the complex imaging mechanism of SAR images and the lack of multi-angle and multi-parameter real scene SAR target data, the generalization performance of existing deep-learning-based synthetic aperture radar (SAR) image target detection methods are extremely limited. In this paper, we propose an unsupervised domain-adaptive SAR ship detection method based on cross-domain feature interaction and data contribution balance. First, we designed a new cross-domain image generation module called CycleGAN-SCA to narrow the gap between the source domain and the target domain. Second, to alleviate the influence of complex backgrounds on ship detection, a new backbone using a self-attention mechanism to tap the potential of feature representation was designed. Furthermore, aiming at the problems of low resolution, few features and easy information loss of small ships, a new lightweight feature fusion and feature enhancement neck was designed. Finally, to balance the influence of different quality samples on the model, a simple and efficient E12IoU Loss was constructed. Experimental results based on a self-built large-scale optical-SAR cross-domain target detection dataset show that compared with existing cross-domain methods, our method achieved optimal performance, with the mAP reaching 68.54%. Furthermore, our method achieved a 6.27% improvement compared to the baseline, even with only 5% of the target domain labeled data.

Mapping of individual sensory nerve axons from digits to spinal cord with the transparent embedding solvent system.

Achieving uniform optical resolution for a large tissue sample is a major challenge for deep imaging. For conventional tissueclearing methods, loss of resolution and quality in deep regions is inevitable due to limited transparency. Here we describe the Transparent Embedding Solvent System (TESOS) method, which combines tissue clearing, transparent embedding, sectioning and block-face imaging. We used TESOS to acquire volumetric images of uniform resolution for an adult mouse whole-body sample. The TESOS method is highly versatile and can be combined with different microscopy systems to achieve uniformly high resolution. With a light sheet microscope, we imaged the whole body of an adult mouse, including skin, at a uniform 0.8 × 0.8 × 3.5 μm3 voxel resolution within 120 h. With a confocal microscope and a 40×/1.3 numerical aperture objective, we achieved a uniform sub-micron resolution in the whole sample to reveal a complete projection of individual nerve axons within the central or peripheral nervous system. Furthermore, TESOS allowed the first mesoscale connectome mapping of individual sensory neuron axons spanning 5 cm from adult mouse digits to the spinal cord at a uniform sub-micron resolution.

The effects of post‐saccadic oscillations on visual processing time

Aims/Purpose: Saccadic eye movements enable us to search for a target of interest in a crowded scene, or in the case of goal‐directed saccades, to bring the peripheral target to the fovea. Visual information is processed quickly at the end of each saccade, yet precise measurements of the times involved remain controversial. This research investigates the time needed to process visual information at the end of each saccade.Methods: A new psychophysical test makes it possible to measure eye movement response latencies and visual processing times. When the test is used in conjunction with an eye tracker, each component that makes up the ‘integrated saccade latency’ (ISL) time, from the onset of the peripheral stimulus to the correct interpretation of the information carried by the stimulus, can be measured and the discrete components delineated. We measured ISL times in six subjects in response to Landolt ring optotypes of varying contrast presented peripherally at an eccentricity of 8° and also at the point of regard (0°).Results: We show that the time required to process and encode the stimulus attribute of interest at the end of a saccade is longer than that needed to carry out the same task in the absence of an eye movement. Depending on the stimulus contrast, these time durations ranged between 101–120 ms (15%) and 34–48 ms (75%) when eye movements were involved and 57–35 (15%) and less than 25 ms (75%) in the absence of eye movements.Conclusions: The extended visual processing times measured when saccades are involved may be the result of transient loss of spatial resolution caused by eyeball instability during post‐saccadic oscillations. These results explain why stimuli of high luminance contrast yield best performance in visual tasks when eye movements are involved.Acknowledgements: We acknowledge the UK Civil Aviation Authority for their support.

Femtosecond reductive Laser Sintering under multiple focus conditions for rapid production of conductive copper layers

Reductive laser sintering is an advantageous alternative to conventional precious metal- or mask-based processes for the electrification of polymers and has been demonstrated in a variety of sensor applications. Ultrashort pulsed lasers promise precise control of the energy applied during sintering and ablation. Besides fine tracks, microelectronic circuits include wide contact pads, which leads to time-consuming processing with small laser spot sizes. The use of larger focal diameters, which results in wider lines and thus a higher metallization rate, is accompanied by a loss of structure resolution. We show the influence of focusing on the femtosecond reductive laser sintering of copper(II) oxide on cyclic olefin copolymers. While small focus diameters down to 23 µm provide high accuracy, increasing the laser power and the focus diameter up to 400 µm significantly accelerates the process, first by enlarging the line width and second by increasing the scanning speed due to the exposure time. Two-dimensional copper electrodes for 23 µm and 200 µm focal diameters were generated by hatching individual lines and compared with respect to their morphology. The enlarged spot can be used for high-speed generation of electrodes with a surface conductivity of 117 mΩ/sq. Hybrid processes with production under combined focusing conditions are presented for the first time.

PS 2 F: Polarized Spiral Point Spread Function for Single-Shot 3D Sensing.

We propose a compact snapshot monocular depth estimation technique that relies on an engineered point spread function (PSF). Traditional approaches used in microscopic super-resolution imaging such as the Double-Helix PSF (DHPSF) are ill-suited for scenes that are more complex than a sparse set of point light sources. We show, using the Cramér-Rao lower bound, that separating the two lobes of the DHPSF and thereby capturing two separate images leads to a dramatic increase in depth accuracy. A special property of the phase mask used for generating the DHPSF is that a separation of the phase mask into two halves leads to a spatial separation of the two lobes. We leverage this property to build a compact polarization-based optical setup, where we place two orthogonal linear polarizers on each half of the DHPSF phase mask and then capture the resulting image with a polarization-sensitive camera. Results from simulations and a lab prototype demonstrate that our technique achieves up to 50% lower depth error compared to state-of-the-art designs including the DHPSF and the Tetrapod PSF, with little to no loss in spatial resolution.

Passive Post-Resonance Tuned Reflectors to Achieve Both 10-bit Phase-Shifting Resolution and Low Insertion Loss Across 20–30 GHz

Passive Post-Resonance Tuned Reflectors to Achieve Both 10-bit Phase-Shifting Resolution and Low Insertion Loss Across 20–30 GHz

The software for improvement of image quality after enlargement

In the paper digital images of various formats were investigated. The different vector image formats have different color rendering capabilities. The main task was to achieve a result of refinement of the random low resolution color raster image without quality and resolution loss. The biggest advantage of using specific vector or compressed raster formats is the ability of scaling without quality loss and comparatively small file size. This eases vector images transfer through networks. In the article a specific algorithm of raster images refinement was investigated, particularly the method of raster images refinement based on combination of interpolation algorithms with and without square root of the color values. The key point of the method is comparison and combination of vertical, horizontal and diagonal interpolation that allows to achieve better precision on color depth calculation. This exact method was never used in commercial of scientific software though there are different variation of combined interpolation methods similar to current one. In this paper two different approaches to image matrix re-calculation during image refinement were tested, in order to research how root squaring the value of color depth would affect the target color value. The result shows that this approach allows to keep more details in shadows and save contours during interpolation though the images lose somewhat of color depth. The experiment shows that this interpolation method with square rooting color values allows to enlarge and refine color images with complex tone curve structure and keep details of the objects in place, though color depth is worsened especially in deepest shades and blacks. On the opposite the method of combined interpolation without root squaring gives significantly better result with color interpolation but loses details in the dark areas of the initial image. The suggested method can be used in a number of different areas

Structural Ambiguity and the Architecture of Language1

AbstractThis article investigates what structural ambiguity reveals about the architecture of language. It analyzes two basic types of structural ambiguity, constituent ambiguity and chain formation ambiguity, and illustrates with a small class of selected case studies how they interweave. It observes that several movement locality constraints have the effect of reducing chain formation ambiguities; however, it argues that movement locality constraints are not primarily motivated to reduce ambiguity. Finally, it defends that structural ambiguity is due to a loss of resolution at the PF branch of the language faculty.

Development and clinical feasibility of a reduced-dose radiograph in children for feeding tube placement.

Temporary feeding tubes are commonly used but may lead to complications if malpositioned. Radiographs are the gold standard for assessing tube position, but clinician concern over radiation risks may curtail their use. We describe development and use of a reduced dose feeding tube radiograph (RDFTR) targeted for evaluation of feeding tube position. Age-based abdominal radiograph was adapted to use the lowest mAs setting of 0.32 mAs with field of view between carina and iliac crests. The protocol was tested in DIGI-13 line-pair plates and anthropomorphic phantoms. Retrospective review of initial clinical use compared dose area product (DAP) for RDFTR and routine abdomen, chest, or infant chest and abdomen. Review of RDFTR reports assessed tube visibility, malpositioning, and incidental critical findings. Testing through a line-pair phantom showed loss of spatial resolution from 2.2 line pairs to 0.6 line pairs but preserved visibility of feeding tube tip in RDFTR protocol. DAP comparisons across 23,789 exams showed RDFTR reduced median DAP 72-93% compared to abdomen, 55-78% compared to chest, and 76-79% compared to infant chest and abdomen (p<0.001). Review of 3286 reports showed tube was visible in 3256 (99.1%), malpositioned in airway 8 times (0.2%) and in the esophagus 74 times (2.3%). The tip was not visualized in 30 (0.9%). Pneumothorax or pneumoperitoneum was noted seven times (0.2%) but was expected or spurious in five of these cases. RDFTR significantly reduces radiation dose in children with temporary feeding tubes while maintaining visibility of tube tip.

Multiscale Fusion of Panchromatic and Multispectral Images Based on Adaptive Iterative Filtering

This paper proposes an efficient and high-fidelity image fusion method based on adaptive smoothing filtering for panchromatic (PAN) and multispectral (MS) image fusion. The scale ratio reflects the ratio of spatial resolution between the panchromatic image and the multispectral image. When facing a multiscale fusion task, traditional methods are unable to simultaneously handle the problems of spectral resolution loss resulting from high scale ratios and the issue of reduced spatial resolution due to low scale ratios. To adapt to the fusion of panchromatic and multispectral satellite images of different scales, this paper improves the problem of the insufficient filtering of high-frequency information of remote sensing images of different scales by the classic filter-based intensity modulation (SFIM) model. It uses Gaussian convolution kernels instead of traditional mean convolution kernels and builds a Gaussian pyramid to adaptively construct convolution kernels of different scales to filter out high-frequency information of high-resolution images. It can adaptively process panchromatic multispectral images of different scales, iteratively filter the spatial information in panchromatic images, and ensure that the scale transformation is consistent with the definition of multispectral images. Using 15 common fusion methods, this paper compares the experimental results of ZY-3 with scale ratio 2.7 and SV-1 with scale ratio 4 data. The results show that the method proposed in this paper retains good spatial information for image fusion at different scales and has good spectral preservation.

Left External Iliac Artery Aneurysm in horse – Case report

An aneurysm is defined as the abnormal and localized dilation of a blood vessel, which can be congenital or acquired. The main consequence is vessel rupture, leading to hemorrhage, hypovolemic shock, and subsequent sudden death. Clinical signs can also be silent or resemble other pathologies, making the diagnosis complex. This study aims to report the clinical case of a Criollo mare diagnosed with an aneurysm of the left external iliac artery, as well as the treatment and diagnostic methods. During the anamnesis, it was observed that the patient experienced episodes of acute abdominal discomfort with rapid and spontaneous resolution, anorexia, and progressive weight loss for approximately a year. Musculoskeletal evaluation revealed grade III lameness in the left pelvic limb. Rectal palpation revealed a parasagittal increase in volume near the lumbosacral segment with a palpable pulse in the region of the left abdominal aorta. Rectal ultrasound with a linear probe (5.5 MHz) revealed decreased and retrograde blood flow compared to the contralateral vessel, suggesting an aneurysm of the left external iliac artery. The prescribed treatment involved the administration of acepromazine, omeprazole, and acetylsalicylic acid for 90 days. Ultrasonography was essential for the final diagnosis and resolution of the reported case, along with the combination of drugs described in the therapeutic protocol.

Bisymmetric pupil modification deconvolution strategy for differential optical transfer function (dOTF) wavefront sensing

Context.The differential optical transfer function (dOTF) is a model-independent image-based wavefront sensor for measuring the complex pupil field (phase and amplitude). This method is particularly suitable for compensating non-common path aberrations or for the phasing of segmented telescopes that often prevent the so-called diffraction-limit resolution from being achieved with real-world instruments.Aims.The main problem inherent to the dOTF approach is to address the effect of the convolution. The resolution of the recovered complex pupil field is impacted by the size of the pupil modification. The complex pupil field estimated by the dOTF is blurred by convolution with the complex conjugate of the pupil modification. If the pupil modification involves a non-negligible region of the pupil (actuator or segment poke), it causes significant blurring and resolution loss.Methods.We propose a bisymmetric pupil modification deconvolution strategy to solve this problem. We use two different dOTFs with the opposite-sign pupil modification to identify the pupil modification location and four dOTFs with a symmetric pupil modification to complete the knowledge of their impact on the complex pupil field prior to the deconvolution process in the Fourier domain. The proposed strategy solves the intrinsic limitation of a former deconvolution algorithm, namely the cross-iteration deconvolution algorithm, which is restricted to amplitude pupil modification and precludes its applicability to phase pupil modification.Results.The bissymetric pupil modification deconvolution strategy is a novel probing pattern that permits the extension of iterative cross-deconvolution to phase-only probes. The effectiveness of the proposed approach has been validated analytically and with numerical simulations.Conclusions.The bisymmetric pupil modification deconvolution strategy can improve the resolution and accuracy of dOTF wavefront sensing and contributes to efficient and precise image-based wavefront sensing techniques.

P113: Psychosocial interventions for dementia grief- a systematic review

Objective:Dementia grief can be described as a caregiver’s anticipatory grief experience due to losses occurring before the care recipient’s physical death. Among other things, these losses can include loss of memory, intimacy, communication, relationship resolution, and family identity. Psychosocial interventions have been developed to address and reduce these pre-loss grief reactions. The objective of this systematic review was to synthesize the evidence on existing dementia grief interventions for caregivers of persons with dementia (PwD).Methods:Electronic databases Web of Science (SSCI), PsycArticles, Psychology and Behavioral Sciences Collection, PsycINFO, PSYNDEX Literature with PSYNDEX Tests and MEDLINE were searched from September 2016 to September 2021. The systematic review was carried out following PRISMA guidelines and it was registered to the PROSPERO database (CRD42021268998). All adult family or friend carers of older persons with dementia were included. All types and severity stages of dementia were included except studies about young onset dementia and dementia grief. Also, family carers could not be bereaved.Results:The 12 included studies contained multifaceted interventions with heterogenous formats. Eight studies had a quantitative, two a qualitative and two a mixed method design. Sample size ranged from two to 273 participants. Interventions included elements of psychoeducation, cognitive and emotional therapeutic strategies based on CBT, acceptance- based and mindfulness-based strategies. The interventions showed statistically significant small to moderate effects on dementia grief. In addition to the effects on dementia grief, the interventions also had a positive impact on mental health-related variables such as burden, depression, empowerment, and resilience.Conclusion:There has been an increase in dementia grief interventions suggesting that dementia grief has been acknowledged as a valid and important construct to describe the dementia caregiver experience. It remains unclear whether health care providers know about and implement elements of the grief interventions in every day clinical encounters with dementia caregivers. Thus, future research should determine the practicing health care providers’ knowledge about dementia grief and its available interventions. Furthermore, it should be examined whether the intervention effects are transferable to caregivers of patients with other terminal illnesses or degenerative disorders, or whether they must be modified.