Search Results (2,213)

Background: This study focuses on the critical task of blood vessel segmentation in medical image analysis, essential for diagnosing cardiovascular diseases and enabling effective treatment planning. Although deep learning architectures often produce very high segmentation results in medical images, coronary computed tomography angiography (CTA) images are more challenging than invasive coronary angiography (ICA) images due to noise and the complexity of vessel structures. Methods: Classical architectures for medical images, such as U-Net, achieve only moderate accuracy, with an average Dice score of 0.722. Results: This study introduces Morpho-U-Net, an enhanced U-Net architecture that integrates advanced morphological operations, including Gaussian blurring, thresholding, and morphological opening/closing, to improve vascular integrity, reduce noise, and achieve a higher Dice score of 0.9108, a precision of 0.9341, and a recall of 0.8872. These enhancements demonstrate superior robustness to noise and intricate vessel geometries. Conclusions: This pre-processing filter effectively reduces noise by grouping neighboring pixels with similar intensity values, allowing the model to focus on relevant anatomical structures, thus outperforming traditional methods in handling the challenges posed by CTA images. Full article

Salt marshes are ecologically and economically valuable ecosystems, yet are vulnerable to marsh dieback, the rapid death of marsh vegetation, which has affected coastal areas along the southeastern and Gulf coasts of the United States in recent decades. This study used multichannel electrical resistivity tomography (ERT) surveys to investigate the shallow hydrostratigraphy (up to 39.2 m depth) of three dieback-affected salt marshes along the Georgia coast to evaluate the influence of site location, vegetation status (dieback versus healthy), and tidal conditions on ERT profiles. ERT profiles revealed consistent subsurface resistivity patterns across the marsh platforms, with low resistivity (0.2 ohm-m) at shallow depths indicating saltwater saturation and a transition to higher resistivity (up to 8.1 ohm-m) at greater depths, potentially signifying a shift to brackish conditions and/or sandy strata. The ERT data indicated that the hydrostratigraphy is similar across all study sites. Furthermore, the ERT data remained consistent regardless of vegetation status, tidal variations, and seasonal changes, suggesting that the processes driving the recovery of marsh dieback are independent of the shallow marsh stratigraphy. These findings enhance our understanding of marsh subsurface conditions, supporting efforts to better understand marsh resilience and guide future research on salt marshes. Full article

The Holy Cross Mountains represent an isolated outcrop of Palaeozoic rocks located in the Trans-European Suture Zone, which is the boundary between the Precambrian East European Craton and Phanerozoic mobile belts of South-Western Europe. Despite extensive structural history studies, high-resolution seismic profiling has not been applied to this region until now. This research introduces near-surface seismic imaging of the Holy Cross Fault, separating two tectonic units of different stratigraphic and deformation history. In our study, we utilize a carefully designed weight drop source survey with 5 m shot and receiver spacing and 4.5 Hz geophones. The imaging technique, combining seismic reflection profiling and travel time tomography, reveals detailed fault geometries down to 400 m. Precise data processing, including static corrections and noise attenuation, significantly enhanced signal-to-noise ratio and seismic resolution. Furthermore, the paper discusses various fault imaging techniques with their shortcomings. The data reveal a complex network of intersecting fault strands, confirming general thrust fault geometry of the fault system, that align with the region’s tectonic evolution. These findings enhance understanding of the Holy Cross Mountains’ structural framework and provide valuable reference data for future studies of similar tectonic environments. Full article

Utilizing short-period dense seismic arrays, ambient noise tomography has proven effective in delineating continuous geological structures, a task critical for characterizing shale gas reservoir configurations. This study deployed 153 short-period seismic stations across the Xiahuayuan District in Zhangjiakou, a region with prospective shale gas deposits, to perform an ambient noise tomography survey. Through a meticulous process involving cross-correlation analysis, dispersion curve extraction, and subsequent inversion, a three-dimensional velocity structure model of the area was constructed. The model discerns subtle velocity changes within the 0–3 km depth interval, achieving a horizontal resolution of approximately 1.5 km in the 0–3 km stratum, thereby effectively delineating the shale reservoir structure. Integration of the velocity model with regional geological data facilitated a comprehensive interpretation and structural analysis of the prospective shale gas zone. Low-velocity anomalies observed within the velocity structure correspond to the spatial distribution of the Xiahuayuan Formation, likely attributable to the prevalent stratum of mudstone shale deposits within this formation. Employing a binary stratigraphic model, the study predicted shale content based on the velocity structure, with predictions exhibiting a moderate correlation (correlation coefficient of 0.58) with empirical data. This suggests the presented method as a viable rapid estimation technique for assessing the shale content of target strata. Full article

Purpose: Augmented reality (AR) may allow vitreoretinal surgeons to leverage microscope-integrated digital imaging systems to analyze and highlight key retinal anatomic features in real time, possibly improving safety and precision during surgery. By employing convolutional neural networks (CNNs) for retina vessel segmentation, a retinal coordinate system can be created that allows pre-operative images of capillary non-perfusion or retinal breaks to be digitally aligned and overlayed upon the surgical field in real time. Such technology may be useful in assuring thorough laser treatment of capillary non-perfusion or in using pre-operative optical coherence tomography (OCT) to guide macular surgery when microscope-integrated OCT (MIOCT) is not available. Methods: This study is a retrospective analysis involving the development and testing of a novel image-registration algorithm for vitreoretinal surgery. Fifteen anonymized cases of pars plana vitrectomy with epiretinal membrane peeling, along with corresponding preoperative fundus photographs and optical coherence tomography (OCT) images, were retrospectively collected from the Mayo Clinic database. We developed a TPU (Tensor-Processing Unit)-accelerated CNN for semantic segmentation of retinal vessels from fundus photographs and subsequent real-time image registration in surgical video streams. An iterative patch-wise cross-correlation (IPCC) algorithm was developed for image registration, with a focus on optimizing processing speeds and maintaining high spatial accuracy. The primary outcomes measured were processing speed in frames per second (FPS) and the spatial accuracy of image registration, quantified by the Dice coefficient between registered and manually aligned images. Results: When deployed on an Edge TPU, the CNN model combined with our image-registration algorithm processed video streams at a rate of 14 FPS, which is superior to processing rates achieved on other standard hardware configurations. The IPCC algorithm efficiently aligned pre-operative and intraoperative images, showing high accuracy in comparison to manual registration. Conclusions: This study demonstrates the feasibility of using TPU-accelerated CNNs for enhanced AR in vitreoretinal surgery. Full article

Background: The caroticoclinoid bar (CCB) or caroticoclinoid foramen (CCF) represents a well-described ossified variant of the skull base. It corresponds to an osseous bridge (resulting after homonymous ligament ossification) between the anterior and middle clinoid processes (ACPs and MCPs) surrounding the internal carotid artery (ICA)’s cavernous segment. Although extensive research has been performed on this clinically significant entity, only a few studies have been conducted on its effect on the ICA. The current study on dried skulls, using computed tomography (CT) and computed tomography angiography (CTA) scans, aimed to investigate the CCB’s presence and potential morphological stenosis patterns. Methods: One hundred (100) dried adult skulls and one hundred sixty (160) skulls from CT scans of patients were obtained (a total of 520 observations). To further calculate the ICA diameter (at the ACP-MCP region) and correlate the resulting dimeters with all potential morphological stenosis patterns of the CCB, thirty (30) CTAs of patients free of the variant were selected. Results: Concerning the osseous pattern morphology, of the total of 520 sides, the CCB was identified in 17.1%, the complete variant (creating a caroticoclinoid foramen-CCF) was calculated in 11.5%, and the incomplete one was calculated in 5.6%. No side, sex, or age impact was identified for the CCB presence. Concerning the ICA dimensions, its diameter was calculated to be between 4 and 5 mm. Thus, we observed three morphological stenosis patterns of the CCF. A low-risk pattern of stenosis (>5 mm diameter) was observed in 40 CCFs (44.9%), an intermediate risk of stenosis (4–5 mm diameter) in 38 CCFs (38.2%), and a high risk of stenosis (<4 mm diameter) was depicted in 15 CCFs (16.8%). Conclusions: In the present study, we investigated the CCF presence and potential morphological stenosis patterns by calculating and correlating the ICA diameter. In 16.8% of the current sample with CCFs (irrespective of their morphology), we observed that the ICA is probably at a high risk of compression. Radiologists and neurosurgeons intervening in the area should preoperatively diagnose the possibility of ICA compression in this area. Full article

To elucidate the potential roles of presynaptic and postsynaptic serotonergic activity in impulsivity traits, we investigated the relationship between self-reported impulsiveness and serotonin transporter (5-HTT) and 5-HT2A receptors in healthy individuals. In this study, 26 participants completed 3-Tesla magnetic resonance imaging and positron emission tomography with [¹¹C]DASB and [¹¹C]MDL100907. To quantify 5-HTT and 5-HT2A receptor availability, the binding potential (BP_ND) of [¹¹C]DASB and [¹¹C]MDL100907 was derived using the simplified reference tissue model with cerebellar gray matter as the reference region. The participants’ impulsivity levels were assessed using the Barratt Impulsiveness Scale-11 (BIS-11). The region of interest (ROI)-based partial correlation analysis with age, sex, and temperament traits as covariates revealed a significant positive correlation between non-planning impulsiveness and [¹¹C]MDL100907 BP_ND in the caudate (CAU) at Bonferroni-corrected p < 0.0045. Non-planning impulsiveness was also positively correlated with [¹¹C]MDL100907 BP_ND in the prefrontal cortex (PFC), ventromedial PFC, orbitofrontal cortex (OFC), insula (INS), amygdala (AMYG), putamen, ventral striatum, and thalamus, and the total score of BIS-11 was positively correlated with [¹¹C]MDL100907 BP_ND in the OFC, INS, AMYG, and CAU at uncorrected p < 0.05. Motor impulsiveness had a positive correlation with [¹¹C]DASB BP_ND in the CAU at uncorrected p < 0.05. Our results suggest that impulsivity traits, characterized by focusing on the present moment without considering future consequences, may be involved in serotonergic neurotransmission, particularly 5-HT2A receptor-mediated postsynaptic signaling in the CAU, which plays an important role in cognitive processes related to executive function, judgment of alternative outcomes, and inhibitory control. Full article

In many soil processes, including solute and gas dynamics, the architecture of intra-aggregate pores is a crucial component. Soil management practices and wetting-drying (W-D) cycles, the latter having a significant impact on pore aggregation, are two key factors that shape pore structure. This study examines the effects of W-D cycles on the architecture of intra-aggregate pores under three different soil management systems: no-tillage (NT), minimum tillage (MT), and conventional tillage (CT). The soil samples were subjected to 0 and 12 W-D cycles, and the resulting pore structures were scanned using X-ray micro-computed tomography, generating reconstructed 3D volumetric data. The data analyses were conducted in terms of multifractal spectra, normalized Shannon entropy, lacunarity, porosity, anisotropy, connectivity, and tortuosity. The multifractal parameters of capacity, correlation, and information dimensions showed mean values of approximately 2.77, 2.75, and 2.75 when considering the different management practices and W-D cycles; 3D lacunarity decreased mainly for the smallest boxes between 0 and 12 W-D cycles for CT and NT, with the opposite behavior for MT. The normalized 3D Shannon entropy showed differences of less than 2% before and after the W-D cycles for MT and NT, with differences of 5% for CT. The imaged porosity showed reductions of approximately 50% after 12 W-D cycles for CT and NT. Generally, the largest pores (>0.1 mm³) contributed the most to porosity for all management practices before and after W-D cycles. Anisotropy increased by 9% and 2% for MT and CT after the cycles and decreased by 23% for NT. Pore connectivity showed a downward trend after 12 W-D cycles for CT and NT. Regarding the pore shape, the greatest contribution to porosity and number of pores was due to triaxial-shaped pores for both 0 and 12 W-D cycles for all management practices. The results demonstrate that, within the resolution limits of the microtomography analysis, pore architecture remained resilient to changes, despite some observable trends in specific parameters. Full article

Separation functions, so-called Tromp functions, are often used to quantitatively analyze the separation behavior in particle processing with respect to individual particle descriptors. However, since the separation behavior of particles is typically influenced by multiple particle descriptors, multivariate Tromp functions are required. This study focuses on methods that allow for the computation of multivariate parametric Tromp functions by means of statistical image analysis and copula-based modeling. The computations are exemplarily performed for the magnetic separation of Li-bearing minerals, including quartz, topaz, zinnwaldite, and muscovite, based on micro-computed tomography images and scanning electron microscopy with energy-dispersive X-ray spectroscopy analysis. In particular, the volume equivalent diameter, zinnwaldite fraction, flatness, and sphericity are examined as possible influencing particle descriptors. Moreover, to compute the Tromp functions, the probability distributions of these descriptors for concentrate and tailing should be used. In this study, 3D image data depicting particles in feed, concentrate, and tailings is available for the computation of Tromp functions. However, concentrate particles tend to be elongated, plate-like, and densely packed, making segmentation for extracting individual particles from image data extremely difficult. Thus, information on the concentrate could not be obtained from the available database. To remedy this, an indirect optimization approach is used to estimate the distribution of particle descriptors of the concentrate. It turned out that this approach can be successfully applied to analyze the influence of size, shape, and composition of particles on their separation behavior. Full article

Measurements of tooth size for estimating inter-arch tooth size discrepancies and inter-tooth distances, essential for orthodontic diagnosis and treatment, are primarily done using traditional methods involving plaster models and calipers. These methods are time-consuming and labor-intensive, requiring multiple steps. With advances in cone-beam computerized tomography (CBCT) and intraoral scanning technology, these processes can now be automated through computer analyses. This study proposes a multi-step computational method for measuring mesiodistal tooth widths and inter-tooth distances, applicable to both CBCT and scan images of plaster models. The first step involves 3D segmentation of the upper and lower teeth using CBCT, combining results from sagittal and panoramic views. For intraoral scans, teeth are segmented from the gums. The second step identifies the teeth based on an adaptively estimated jaw midline using maximum intensity projection. The third step uses a decentralized convolutional neural network to calculate key points representing the parameters. The proposed method was validated against manual measurements by orthodontists using plaster models, achieving an intraclass correlation coefficient of 0.967 and a mean absolute error of less than 1 mm for all tooth types. An analysis of variance test confirmed the statistical consistency between the method’s measurements and those of human experts. Full article

Background: The orthodontic management of pediatric patients with rare diseases, such as Ectodermal Dysplasia (ED) and Osteogenesis Imperfecta (OI), requires complex protocols due to dental anomalies in both the number and structure of teeth. These conditions necessitate a departure from traditional orthodontic approaches, as skeletal anchoring is often required because of these anomalies. Case Presentation: A patient with ED, characterized by hypodontia and malformed teeth, presented with insufficient natural teeth for anchorage. This challenge was addressed using a Maxillary Skeletal Expander (MSE) with miniscrews. Cone-beam computed tomography (CBCT) and cephalometric radiographs were used to assess bone density, which guided the creation of a customized hybrid device. A second patient with OI, a condition causing fragile bones, had malformed teeth and a high risk of fractures. Skeletal anchoring with MSE and miniscrews was chosen to avoid damaging brittle bones. The fragile nature of the patient’s bones required careful planning and close monitoring throughout the treatment process. Both patients were treated at the UOC of Pediatric Dentistry, Sapienza University of Rome, using MSE with miniscrews. Pre- and post-treatment imaging (CBCT and cephalometric radiographs) were used to evaluate bone quality and monitor progress. Skeletal anchoring successfully addressed the unique challenges in both cases, achieving outcomes comparable to those in unaffected patients. Discsussions: despite limited bone volume, MSE successfully achieved maxillary arch expansion and improved occlusion. Post-treatment radiographs showed successful maxillary expansion and alignment without complications. Conclusions: This case series highlighted the effectiveness of MSE with miniscrews in treating patients with rare diseases. It advances orthodontic management by offering reliable solutions for complex cases involving dental anomalies and compromised bone structures. Full article

Background: To investigate functional and anatomical outcomes after pars plana vitrectomy (PPV) for lamellar macular hole (LMH) with a long-term follow-up. Methods: An interventional study on 14 patients (16 eyes) with LMH was conducted. The inclusion criteria included a minimum 36-month follow-up after PPV. The preoperative and postoperative best-corrected visual acuity (BCVA) and spectral domain optical coherence tomography parameters were examined. Results: Preoperatively, the mean BCVA was 0.46 ± 0.22 LogMAR. Epiretinal proliferation (ERP) was visible in 81.25% of eyes. Outer retinal disruption was present in 31.25% of LMH cases. The average central foveal thickness (CFT) measured 183.68 ± 61.73 microns. The mean BCVA improved at each follow-up time point: it was 0.24 ± 0.16 LogMAR at 1 month, 0.18 ± 0.15 LogMAR at 6 months, and 0.09 ± 0.11 LogMAR at the last follow-up. There was a statistically significant improvement between BCVA at 1 month and BCVA at 6 months and between BCVA at 6 months and BCVA at the last follow-up (p < 0.001). BCVA improved in all eyes, with 87.5% achieving at least 0.3 LogMAR improvement. The mean CFT at the 1-month follow-up was 211.45 ± 43.55 microns, increased to 248.81 ± 48.51 microns at 6 months, and further increased to 278.37 ± 45.50 microns at the last follow-up. Foveal contour restoration was achieved in all eyes, and those with preoperative ellipsoid zone alterations demonstrated a complete repair of the external retinal layers. No intra or postoperative complications were recorded. Conclusions: In our series, PPV had a high success rate and was associated with a substantial functional improvement in LMH treatment, and this result was maintained and kept increasing until the last follow-up. Long-term follow-up is crucial for a comprehensive evaluation of the healing process and to assess the benefits of the surgical intervention. Full article

Background/Objectives: To develop and validate a model system using deep learning algorithms for the automatic detection of type A aortic dissection (AD), and differentiate it from normal and type B AD patients. Methods: In this retrospective study, a deep learning model is developed, based on aortic computed tomography angiography (CTA) scans of 498 patients using training, validation and test sets of 398, 50 and 50 patients, respectively. An independent test set of 316 patients is used to validate and evaluate its performance. Results: Our model comprises two components. The first one is an objection detection model, which can identify the aorta from CTA. The second one is a dissection classification model, which can automatically detect the presence of aortic dissection and determine its type based on Stanford classification. Overall, the sensitivity and specificity for Type A AD were 0.969 and 0.982, for Type B AD were 0.946 and 0.996 and for normal cases were 0.988 and 1.000, respectively. The average processing time per CTA scan was 7.9 ± 2.8 s. (mean ± standard deviation). Conclusions: This deep learning automatic model can accurately and quickly detect type A AD patients, and could serve as an imaging triage in an emergency setting and facilitate early intervention and surgery to decrease the mortality rates of type A AD patients. Full article

Objectives: This study aims to develop and validate a standardized methodology for creating high-fidelity, custom-made, patient-specific 3D-printed vascular models that serve as tools for preoperative planning and training in the endovascular treatment of peripheral artery disease (PAD). Methods: Ten custom-made 3D-printed vascular models were produced using computed tomography angiography (CTA) scans of ten patients diagnosed with PAD. CTA images were analyzed using Syngo.via by a specialist to formulate a medical prescription that guided the model’s creation. The CTA data were then processed in OsiriX MD to generate the .STL file, which is further refined in a Meshmixer. Stereolithography (SLA) 3D printing technology was employed, utilizing either flexible or rigid materials. The dimensional accuracy of the models was evaluated by comparing their CT scan images with the corresponding patient data, using OsiriX MD. Additionally, both flexible and rigid models were evaluated by eight vascular surgeons during simulations in an in-house-designed setup, assessing both the technical aspects and operator perceptions of the simulation. Results: Each model took approximately 21.5 h to fabricate, costing €140 for flexible and €165 for rigid materials. Bland–Alman plots revealed a strong agreement between the 3D models and patient anatomy, with outliers ranging from 4.3% to 6.9%. Simulations showed that rigid models performed better in guidewire navigation and catheter stability, while flexible models offered improved transparency and lesion treatment. Surgeons confirmed the models’ realism and utility. Conclusions: The study highlights the cost-efficient, high-fidelity production of 3D-printed vascular models, emphasizing their potential to enhance training and planning in endovascular surgery. Full article

The distribution of water droplets in crude oil is one of the key issues involved in the processes of oil extraction and transportation, and these water droplets might also be habitats for microorganisms in oil reservoirs. However, it is still a challenge to observe and measure the distribution of water droplets in crude oil quickly and directly. In this work, an improved method based on the optical microscopy technique is introduced, which is named the Plate Pressing (PP) method and can observe and determine the distribution of water droplets in crude oil directly. The reliability of this method was verified by comparing the results with those of a computed tomography (CT) scan, indicating that the PP method can measure the distribution of water droplets accurately. Meanwhile, the total number and size distribution of water droplets in three crude oil samples from different oilfields were obtained by the PP method, which consolidated the idea that the PP method is capable of determining the distribution of the water droplets in crude oil directly and is suitable for the statistical analysis of water droplets in multiple samples of crude oil. Full article