Antepartum Intimate Partner Violence: Development of a Risk Prediction Model.

Objectives: To explore socio-behavioral, clinical, and imaging findings associated with antepartum intimate partner violence (IPV) and aid in risk stratification of at-risk individuals. Methods: We analyzed electronic medical records during indexed pregnancies for 108 pregnant patients who self-reported antepartum IPV (cases) and 106 age-matched pregnant patients who did not self-report antepartum IPV (controls). Sociodemographic, clinical, and radiology data were analyzed via chi-squared and Fisher's exact tests with p < 0.05 as the threshold for significance. Stepwise logistic regression was applied to derive a risk prediction model. Results: The proportion of cases reporting emotional IPV (76% vs. 52%) and/or physical IPV (45% vs. 31%) during pregnancy significantly increased from prior to pregnancy. Cases were significantly more likely to report prepregnancy substance use (odds ratio [OR] = 2.60; 95% confidence interval [CI]: 1.13-5.98), sexually transmitted infections (OR = 3.48; 95%CI: 1.64-7.37), abortion (OR = 3.17; 95%CI: 1.79, 5.59), and preterm birth (OR = 5.97; 95%CI: 1.69-21.15). During pregnancy, cases were more likely to report unstable housing (OR = 5.26; 95%CI: 2.67-10.36), multigravidity (OR = 2.83; 95%CI: 1.44-5.58), multiparity (OR = 3.75; 95%CI: 1.72-8.20), anxiety (OR = 3.35; 95%CI: 1.85-6.08), depression (OR = 5.58; 95%CI: 3.07-10.16), substance use (OR = 2.92; 95%CI: 1.28-6.65), urinary tract infection (UTI) (OR = 3.26; 95%CI: 1.14-9.32), intrauterine growth restriction (OR = 10.71; 95%CI: 1.35-85.25), and cesarean delivery (OR = 2.25; 95%CI: 1.26-4.02). Cases had significantly more OBGYN abnormalities on imaging and canceled more radiological studies (OR = 5.31). Logistic regression found housing status, sexually transmitted infection history, preterm delivery history, abortion history, depression, and antepartum UTI predictive of antepartum IPV. The risk prediction model achieved good calibration with an area under the curve of 0.79. Conclusions: This study identifies significant disparities among patients experiencing antepartum IPV, and our proposed risk prediction model can inform risk assessment in this setting.

Injury patterns and demographics in older adult abuse and falls: A comparative study in emergency department settings.

BACKGROUND: Falls and interpersonal violence pose significant threats to older adults, leading to injuries, hospitalizations, and emergency department (ED) visits. This study investigates the demographics and injury patterns in older adults (aged 60 and above) who sought ED care due to assaults, comparing them with those who experienced falls to gain a deeper understanding of older adult abuse patterns. METHOD: This study utilizes data from the National Electronic Injury Surveillance System (NEISS) All Injury Program (2005-2019) to examine injuries among older adults aged 60 years and above. Participants were categorized into two groups: older adult abuse and injuries due to falls. The differences between the groups by demographics, injury locations, patterns, and temporal trends were analyzed using statistical methods accounting for the weighted stratified nature of the data. Cosinor analysis and Joinpoint regression were used for temporal analysis. RESULTS: Over 15 years, there were an estimated 307,237 ED visits for older adult abuse and 39,477,217 for falls. Older adults experiencing abuse were younger and had lower hospital admission rates compared to fall patients. Injuries associated with abuse included contusions/abrasions, penetrating injuries, and fractures to the head/neck, fingers, toes, ribs, and lower extremities. In contrast, fall patients had higher admission rates, with more fractures, including cervical spine and hip fractures. Temporal patterns showed a higher rate of assaults during the summer, whereas abuse demonstrated bimodal peaks in the summer and fall. CONCLUSIONS: Injuries associated with abuse such as facial, upper trunk, and upper extremity fractures should raise suspicion even in the absence of severe symptoms. These findings emphasize the importance of early identification to connect older adults with support resources, as patients experiencing abuse often get discharged from the ED.

Effect of the NFL's Super Bowl on emergency department visits for assault-related injuries.

PURPOSE: Through its associations with mass gatherings, alcohol consumption, emotional cues, and gambling, the Super Bowl (SB) has been implicated in increased rates of interpersonal violence and assaults. This study endeavors to investigate the relationship between assault-related injuries, especially intimate partner violence (IPV) and SB. METHOD: A retrospective review of prospectively collected data from the National Electronic Injury Surveillance System (NEISS) spanning 2005 to 2017 was conducted. Assault-related injuries were examined in relation to (1) the 4-day Super Bowl weekend (Friday-Monday), (2) Super Bowl Sunday, and (3) the Super Bowl week (Friday-Thursday) for all years, following the loss of the projected winning team (underdog victories), and losses despite a significant point spread favoring one team (upset losses). National estimates of injuries and associated variables were derived using the SUDAAN software. RESULTS: While there were no significant differences in the overall number of assaults or assault types during the SB weekend (5.6% vs 5.5%; p = 0.31), relative decreases were observed for altercations (21.1% vs 24.8%; p < 0.01), sexual assault (3.4% vs 4.0%; p < 0.01), and IPV (8.3% vs 12.5%; p < 0.01) on the Friday preceding SB, and robbery incidents on SB Sunday (2.1% vs 3.5%; p = 0.01). No changes in the incidence of assault-related injuries were found based on the favored or underdog status of the teams, including upset losses. CONCLUSION: Contrary to expectations, SB was not associated with increased assault-related injuries. This study underscores the need for year-round structural changes in addressing violence rather than relying solely on heightened awareness during specific events.

Assault-related anoxia and neck injuries in US emergency departments.

BACKGROUND: Early identification of non-fatal strangulation in the context of intimate partner violence (IPV) is crucial due to its severe physical and psychological consequences for the individual experiencing it. This study investigates the under-reported and underestimated burden of IPV-related non-fatal strangulation by analysing assault-related injuries leading to anoxia and neck injuries. METHODS: An IRB-exempt, retrospective review of prospectively collected data were performed using the National Electronic Injury Surveillance System All Injury Programme data from 2005 to 2019 for all assaults resulting in anoxia and neck injuries. The type and mechanism of assault injuries resulting in anoxia (excluding drowning, poisoning and aspiration), anatomical location of assault-related neck injuries and neck injury diagnosis by morphology, were analysed using statistical methods accounting for the weighted stratified nature of the data. RESULTS: Out of a total of 24 493 518 assault-related injuries, 11.6% (N=2 842 862) resulted from IPV (defined as perpetrators being spouses/partners). Among 22 764 cases of assault-related anoxia, IPV accounted for 40.4%. Inhalation and suffocation were the dominant mechanisms (60.8%) of anoxia, with IPV contributing to 41.9% of such cases. Neck injuries represented only 3.0% of all assault-related injuries, with IPV accounting for 21% of all neck injuries and 31.9% of neck contusions. CONCLUSIONS: The study reveals a significant burden of IPV-related anoxia and neck injuries, highlighting the importance of recognising IPV-related strangulation. Comprehensive screening for IPV should be conducted in patients with unexplained neck injuries, and all IPV patients should be screened for strangulation events.

Labor trafficking in marijuana production: a hidden epidemic in the shadows of the cannabis industry.

Labor trafficking in marijuana production remains a concealed epidemic within the expanding cannabis industry. This abstract brings attention to the systemic exploitation of vulnerable individuals engaged in cultivating, harvesting, and processing cannabis. It explores the factors contributing to labor trafficking, including demand for cheap labor, inadequate regulation, and the vulnerability of the workforce. By compiling published cases, both in peer-reviewed literature and the media, this perspective piece investigates the extent of health issues experienced by labor-trafficked victims. These include chronic pain from repetitive tasks, respiratory problems due to exposure to pesticides and other toxic substances, musculoskeletal injuries, malnutrition, and mental health disorders stemming from trauma and extreme stress. Additionally, this perspective article examines the factors contributing to poor health outcomes of labor-trafficked victims, including hazardous working conditions, lack of access to healthcare, and physical and psychological abuse. Addressing the health challenges faced by labor-trafficked victims in the cannabis industry requires multidimensional solutions: awareness among healthcare providers, comprehensive medical services, and mental health support. Furthermore, collaborative efforts among government agencies, healthcare providers, labor organizations, and the cannabis industry are essential in preventing trafficking and addressing the health disparities faced by labor-trafficked victims.

Understanding Health Care Utilization and Occupational Exposures of Labor-Trafficked People.

OBJECTIVES: To describe health care utilization and occupational exposures during trafficking among foreign-born people labor-trafficked in the U.S. METHODS: Retrospective analysis of immigration files for health data among 114 labor-trafficked individuals. RESULTS: Mean age was 30. Files of 38% mentioned accessing medical services at least once, mostly via hospitals (73%-81%). Forty-three percent (43%) had U.S. citizen children-indicating their children and spouses interacted with social and medical systems during exploitation. Almost all (97%) had limited English proficiency, and 75% did not have legal immigration status. Employers/traffickers interfered with access to health care and forced victims to work while injured. Half (50%) had sick family members. Victims reported physical and sexual abuse, toxic and environmental occupational exposures, and sleep disturbances. CONCLUSIONS: This is the largest study to elucidate health concerns and care utilization patterns among labor-trafficked people. Concerted resources must be dedicated to understanding health needs and health systems intervention opportunities for labor-trafficked people.

Trauma and female reproductive health across the lifecourse: motivating a research agenda for the future of women's health.

The aetiology behind many female reproductive disorders is poorly studied and incompletely understood despite the prevalence of such conditions and substantial burden they impose on women's lives. In light of evidence demonstrating a higher incidence of trauma exposure in women with many such disorders, we present a set of interlinked working hypotheses proposing relationships between traumatic events and reproductive and mental health that can define a research agenda to better understand reproductive outcomes from a trauma-informed perspective across the lifecourse. Additionally, we note the potential for racism to act as a traumatic experience, highlight the importance of considering the interaction between mental and reproductive health concerns, and propose several neuroendocrinological mechanisms by which traumatic experiences might increase the risk of adverse health outcomes in these domains. Finally, we emphasize the need for future primary research investigating the proposed pathways between traumatic experiences and adverse female reproductive outcomes.

Maternal Health Concerns for Pregnant Labor-Trafficked People: A Scoping Review.

We set out to map the (1) living/occupational hazards, (2) health outcomes, and (3) barriers to care that exist for pregnant labor-trafficked people. Eight databases were systematically searched based on inclusion criteria. Five papers were eligible for inclusion. Data on study characteristics, social determinants, hazardous exposures, health outcomes, and barriers to care were extracted and synthesized. Common risk factors and occupational/living hazards were identified. Both were thematically connected with barriers to care and a host of adverse health outcomes. More importantly, a significant gap was discovered with no disaggregated quantitative data on the experience of pregnancy among labor-trafficked people. The interaction of risk factors, occupational/living hazards, and barriers to care experienced by pregnant labor-trafficked people may influence their susceptibility to adverse health outcomes. We need population-based studies, informed by those with lived experience of labor trafficking to examine the experience of pregnancy for labor-trafficked people to improve intervention and support efforts for this population.

"Praying for freedom": a story of labor trafficking during pregnancy.

Given the scant literature and data that exist on labor trafficking in general, obstetricians and gynecologists have very limited awareness of the effect of pregnancy on individuals affected by labor trafficking. Labor trafficking is the use of force, fraud, or coercion to compel an individual to provide a service. Our current understanding of this topic lacks the narratives of survivors who have lived experiences with this intersection. This study presented the story of a labor-trafficked person navigating the healthcare system throughout her pregnancy to shed light on an important presentation of labor trafficking in women's healthcare settings. The insufficient attention afforded to and the stereotypical views of labor trafficking do not often include the experiences of pregnant women. Therefore, presenting examples of labor trafficking, such as in this case study, are important to combat implicit structural and institutional biases that interfere with survivor identification. In addition to sharing one survivor's story, this article presents a trauma-informed approach to setting up socioculturally sensitive, developmentally appropriate, and inherently empowering conversations within healthcare settings to assess for exploitation and connect victims to resources. This case and framework are very important for obstetrician-gynecologists as they are uniquely positioned to screen and care for pregnant labor-trafficked people. Given the well-described "dual exploitation" of those experiencing intimate partner abuse and trafficking, clinical settings that focus on women's health and reproductive healthcare are important touchpoints for the identification, resource coordination, and management of pregnant-trafficked people.

Holiday effect on injuries sustained by assault victims seen in US emergency departments.

PURPOSE: There has been a limited and inconsistent analysis of assault-related injury patterns associated with holidays. We investigated the temporal variation in assault-related injuries presenting to US emergency departments (ED) around holidays. METHODS: We examined data from the National Electronic Injury Surveillance System Database between 2005 and 2017 for six categories of assault-related injuries: altercation, sexual assault, robbery, intimate partner violence (IPV), other specified, and unknown. Differences between holiday and non-holiday periods were analyzed for each assault type. RESULTS: There was a significant difference in overall assault-related injury visits between holiday and non-holiday periods (p < 0.00001). Of over 21 million assault-related injury visits, 14.9% occurred during holiday periods and 85% during non-holiday periods. The difference between the daily number of assault-related ED visits was also significantly higher during the holiday period than baseline non-holiday period (p < 0.00001). Altercations and IPV were significantly higher than baseline for New Year's Eve (highest), St. Patrick's Day, July 4th, and Labor Day. IPV also remained significantly higher than baseline during Thanksgiving and Christmas. Sexual assaults were significantly higher than baseline during the New Year's Eve period but lower than baseline during Christmas and Easter. CONCLUSIONS: Holidays are associated with increase in several assault-related injuries. The information can help allocate healthcare resources and guide prevention strategies.

There is more to the story.

For most patients, primary care and generalist settings are the first clinical touchpoints to accessing medical care. As such, they present the formative opportunity for stories to be communicated and trust to be developed between patients and the health care system. The skills of listening, supporting, communicating, and empathizing are essential in providing patient care and promoting strong patient-physician relationships. They are particularly crucial for people who have experienced interpersonal violence. In this piece, I reflect on my experience as a crisis counselor working with an underage survivor of sexual violence. This encounter provides an application of trauma-informed approaches to caring for survivors of violence and contextualizes the effects of intergenerational trauma. Narratives like this one shed a timely, sorely needed light on the role of physicians in understanding and intervening upon the cycle of violence. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Human trafficking and the growing malady of disinformation.

Disinformation has endangered the most vulnerable communities within our world. The anti-trafficking movement in particular has been adversely impacted by disinformation tactics advanced through the QAnon campaign. QAnon's extremist messaging exacerbates gendered, racist, and xenophobic manifestations of trafficking victimization as well as problematic responses to trafficking that underpin historic structural inequities built into the United States' response to trafficking. We describe an overview of mechanisms used by the QAnon campaign to spread disinformation and illustrate how these mechanisms adversely affect the anti-trafficking movement. Given the critical role of healthcare providers in both the identification and connection to care for trafficked persons, as well as their susceptibility to disinformation, we provide several recommendations for the health sector to leverage their educational and advocacy power to combat trafficking disinformation while addressing the root causes of human trafficking.

Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging.

SIGNIFICANCE: Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image representation. Nonlinear optical fluence correction in OA imaging is highly ill-posed, leading to the inaccurate recovery of optical absorption maps. This work aims to recover the optical absorption maps using deep learning (DL) approach by correcting for the fluence effect. AIM: Different DL models were compared and investigated to enable optical absorption coefficient recovery at a particular wavelength in a nonhomogeneous foreground and background medium. APPROACH: Data-driven models were trained with two-dimensional (2D) Blood vessel and three-dimensional (3D) numerical breast phantom with highly heterogeneous/realistic structures to correct for the nonlinear optical fluence distribution. The trained DL models such as U-Net, Fully Dense (FD) U-Net, Y-Net, FD Y-Net, Deep residual U-Net (Deep ResU-Net), and generative adversarial network (GAN) were tested to evaluate the performance of optical absorption coefficient recovery (or fluence compensation) with in-silico and in-vivo datasets. RESULTS: The results indicated that FD U-Net-based deconvolution improves by about 10% over reconstructed optoacoustic images in terms of peak-signal-to-noise ratio. Further, it was observed that DL models can indeed highlight deep-seated structures with higher contrast due to fluence compensation. Importantly, the DL models were found to be about 17 times faster than solving diffusion equation for fluence correction. CONCLUSIONS: The DL methods were able to compensate for nonlinear optical fluence distribution more effectively and improve the optoacoustic image quality.

Model resolution matrix based deconvolution improves over non-quadratic penalization in frequency-domain photoacoustic tomography.

Frequency domain photoacoustic tomography is becoming more attractive due to low-cost and compact light-sources being used; however, frequency-domain implementation suffers from lower signal to noise compared to time-domain implementation. In this work, we have developed a non-quadratic based penalization framework for frequency-domain photoacoustic imaging, and further proposed a two-step model-resolution matrix based deconvolution approach to improve the reconstruction image quality. The model-resolution matrix was developed in the context of different penalty functions like l2-norm, l1-norm, Cauchy, and Geman-McClure. These model-resolution matrices were then used to perform the deconvolution operation using split augmented Lagrangian shrinkage thresholding algorithm in both full-view and limited-view configurations. The results indicated that the two-step approach outperformed the different penalty function (prior constraint) based reconstruction, with an improvement of about 20% in terms of peak signal to noise ratio and 30% in terms of structural similarity index measure. The improved image quality provided using these algorithms will have a direct impact on realizing practical frequency-domain implementation in both limited-view and full-view configurations.

Assault related injury visits in US emergency departments: An analysis by weekday, month and weekday-by-month.

This study investigated the temporal variation (month and day) in assault-related injuries presenting to the US Emergency Departments (ED). An IRB exempt, retrospective review of prospectively collected data was performed using the National Electronic Injury Surveillance System Database from 2005 to 2017 for six categories of assault-related injuries-altercation, sexual assault, robbery, intimate partner violence (IPV), other specified assaults and unknown assault types. National estimates of injuries and associated variables were obtained using SUDAAN software, followed by cosinor analyses for the variation of month and weekday of injury. Three-dimensional topographic representations for weekday-by-month analyses were also created. Over this 13-year time span, there were more than 21 million injury visits due to assault, accounting for 6.57% of all ED visits. While there was no change in the incidence of total number of assaults over the study period, there was a significant increase in the annual percentage incidence of IPV (1.17%; p = .0094) and robbery (2.56%; p = .0001). Cosinor analyses demonstrated a mid-summer peak for all assault types except for robberies (late summer). All assault types showed a weekend peak (late Saturday or early Sunday). Topographical contours exhibited a peak in July and August on early Sunday for all assaults, however the month varied by the type of assault, with weekend peaks in the spring and winter for IPV. This information can be used in prospective resource planning for management and prevention strategies.

Siamese-SR: A Siamese Super-Resolution Model for Boosting Resolution of Digital Rock Images for Improved Petrophysical Property Estimation.

Digital Rock Physics leverages advances in digital image acquisition and analysis techniques to create 3D digital images of rock samples, which are used for computational modeling and simulations to predict petrophysical properties of interest. However, the accuracy of the predictions is crucially dependent on the quality of the digital images, which is currently limited by the resolution of the micro-CT scanning technology. We have proposed a novel Deep Learning based Super-Resolution model called Siamese-SR to digitally boost the resolution of Digital Rock images whilst retaining the texture and providing optimal de-noising. The Siamese-SR model consists of a generator which is adversarially trained with a relativistic and a siamese discriminator utilizing Materials In Context (MINC) loss estimator. This model has been demonstrated to improve the resolution of sandstone rock images acquired using micro-CT scanning by a factor of 2. Another key highlight of our work is that for the evaluation of the super-resolution performance, we propose to move away from image-based metrics such as Structural Similarity (SSIM) and Peak Signal to Noise Ratio (PSNR) because they do not correlate well with expert geological and petrophysical evaluations. Instead, we propose to subject the super-resolved images to the next step in the Digital Rock workflow to calculate a crucial petrophysical property of interest, viz. porosity and use it as a metric for evaluation of our proposed Siamese-SR model against several other existing super-resolution methods like SRGAN, ESRGAN, EDSR and SPSR. Furthermore, we also use Local Attribution Maps to show how our proposed Siamese-SR model focuses optimally on edge-semantics, which is what leads to improvement in the image-based porosity prediction, the permeability prediction from Multiple Relaxation Time Lattice Boltzmann Method (MRTLBM) flow simulations as well as the prediction of other petrophysical properties of interest derived from Mercury Injection Capillary Pressure (MICP) simulations.

Weighted model-based optoacoustic reconstruction for partial-view geometries.

Acoustic heterogeneities in biological samples are known to cause artifacts in tomographic optoacoustic (photoacoustic) image reconstruction. A statistical weighted model-based reconstruction approach was previously introduced to mitigate such artifacts. However, this approach does not reliably provide high-quality reconstructions for partial-view imaging systems, which are common in preclinical and clinical optoacoustics. In this article, the capability of the weighted model-based algorithm is extended to generate optoacoustic reconstructions with less distortions for partial-view geometry data. This is achieved by manipulating the weighting scheme based on the detector geometry. Using partial-view optoacoustic tomography data from a tissue-mimicking phantom containing a strong acoustic reflector, tumors grafted onto mice, and a mouse brain with intact skull, the proposed partial-view-corrected weighted model-based algorithm is shown to mitigate reflection artifacts in reconstructed images without distorting structures or boundaries, compared with both conventional model-based and the weighted model-based algorithms. It is also demonstrated that the partial-view-corrected weighted model-based algorithm has the additional advantage of suppressing streaking artifacts due to the partial-view geometry itself in the presence of a very strong optoacoustic chromophore. Due to its enhanced performance, the partial-view-corrected weighted model-based algorithm may prove useful for improving the quality of partial-view multispectral optoacoustic tomography, leading to enhanced visualization of functional parameters such as tissue oxygenation.

"Because the resources aren't there, then we fail. We fail as a society": A Qualitative Analysis of Human Trafficking Provider Perceptions of Child Welfare Involvement among Trafficked Mothers.

BACKGROUND: Little is understood about child welfare involvement (CWI) in cases where the birth mother has experienced human trafficking. OBJECTIVES: The aim of this study was to explore provider perceptions of the impact of CWI for the trafficked mother. METHODS: Participants were selected among providers caring for trafficked birth mothers. Semi-structured interviews were conducted with providers and qualitative content analysis was conducted. RESULTS: Interviewees reported reasons for CWI, positive and negative impacts of CWI and provided recommendations for systems improvement. CONCLUSION FOR PRACTICE: Recommendations from this exploratory study include mechanisms to support trafficked mothers, train hospital social workers, and systems change. During the prenatal period, strategies to support the trafficked mother may include addressing gaps in social determinants of health, ensuring appropriate medical and mental health care, early screening and referral to substance use treatment services, enhancing community support, and working to develop safety plans for survivors and their families. Enhanced engagement of social workers and all providers to improve understanding of the unique complexity of trafficked mothers is needed. Education should include an understanding that judgement of a caretaker's ability to parent should be current and holistic and not reflexive based on history in the electronic medical record. An exploration of the child welfare system itself should also be undertaken to identify and modify discriminatory laws and policies. Finally, efforts to address social determinants of health in the community and enhance the trauma-informed nature of child welfare referrals could improve the lives of trafficked mothers.

Reporter gene-based optoacoustic imaging of E. coli targeted colon cancer in vivo.

Bacteria-mediated cancer-targeted therapy is a novel experimental strategy for the treatment of cancers. Bacteria can be engineered to overcome a major challenge of existing therapeutics by differentiating between malignant and healthy tissue. A prerequisite for further development and study of engineered bacteria is a suitable imaging concept which allows bacterial visualization in tissue and monitoring bacterial targeting and proliferation. Optoacoustics (OA) is an evolving technology allowing whole-tumor imaging and thereby direct observation of bacterial colonization in tumor regions. However, bacterial detection using OA is currently hampered by the lack of endogenous contrast or suitable transgene fluorescent labels. Here, we demonstrate improved visualization of cancer-targeting bacteria using OA imaging and E. coli engineered to express tyrosinase, which uses L-tyrosine as the substrate to produce the strong optoacoustic probe melanin in the tumor microenvironment. Tumors of animals injected with tyrosinase-expressing E. coli showed strong melanin signals, allowing to resolve bacterial growth in the tumor over time using multispectral OA tomography (MSOT). MSOT imaging of melanin accumulation in tumors was confirmed by melanin and E. coli staining. Our results demonstrate that using tyrosinase-expressing E. coli enables non-invasive, longitudinal monitoring of bacterial targeting and proliferation in cancer using MSOT.

Multi GPU parallelization of maximum likelihood expectation maximization method for digital rock tomography data.

Digital rock is an emerging area of rock physics, which involves scanning reservoir rocks using X-ray micro computed tomography (XCT) scanners and using it for various petrophysical computations and evaluations. The acquired micro CT projections are used to reconstruct the X-ray attenuation maps of the rock. The image reconstruction problem can be solved by utilization of analytical (such as Feldkamp-Davis-Kress (FDK) algorithm) or iterative methods. Analytical schemes are typically computationally more efficient and hence preferred for large datasets such as digital rocks. Iterative schemes like maximum likelihood expectation maximization (MLEM) are known to generate accurate image representation over analytical scheme in limited data (and/or noisy) situations, however iterative schemes are computationally expensive. In this work, we have parallelized the forward and inverse operators used in the MLEM algorithm on multiple graphics processing units (multi-GPU) platforms. The multi-GPU implementation involves dividing the rock volumes and detector geometry into smaller modules (along with overlap regions). Each of the module was passed onto different GPU to enable computation of forward and inverse operations. We observed an acceleration of [Formula: see text] times using our multi-GPU approach compared to the multi-core CPU implementation. Further multi-GPU based MLEM obtained superior reconstruction compared to traditional FDK algorithm.