Restoration Techniques Research Articles

The "Smile Design and Space" Concept for Altering Vertical Dimension of Occlusion and Esthetic Restorative Material Selection.

This article introduces the smile design and space (SDS) concept for managing the vertical dimension of occlusion (VDO) in full-mouth reconstructions and its influence on the selection of esthetic restorative materials. Limitations of traditional VDO adjustment methods are being addressed through a facially driven treatment approach that enhances esthetics improves function and minimizes invasiveness. The SDS concept involves detailed evaluations of the incisal edges of the maxillary central incisors in relation to the upper lip at rest and at full smile. This includes analyzing variations in incisal exposure due to differing lip mobility, which can significantly impact gingival esthetics, particularly in cases with gingival exposure during smiling. The concept employs a strategic formula to determine the necessary alterations in VDO based on specific dental relationships and wear patterns. The SDS concept provides guidelines for full-mouth reconstructions, emphasizing minimal invasiveness and the integration of esthetics with functional dynamics to enhance the predictability of clinical outcomes and reduce complications associated with traditional restoration techniques. The SDS concept enhances the precision of full-mouth reconstructions through individualized adjustment of the VDO, tailored to the esthetic and functional requirements of each patient.

From reduction to rebalancing: Insights into the long-term effects of sediment dredging on nitrogen transformations in river ecosystems

Although sediment dredging is a widely employed water management and restoration technique for the removal of internal nitrogen (N), the long-term effects of dredging on N transformation in dredged rivers remain largely undetermined. In this study, we investigated the effects of dredging on N transformation processes spanning three years at ten sites in the purple-soil watershed within the middle reaches of the Fu River Basin. We combined isotopic and molecular techniques to provide novel insights into the interactions associated with microbial utilization capacities between sediment and river water before, during, and after dredging. Initially, dredging was found to significantly reduce the total nitrogen content by approximately 75 %, although over time, there was a slight increase in concentrations. Secondly, significant reductions in microbial richness and diversity were detected in both river water and sediment, with 39 classes reduced, 12 new classes emerging, and an increase in archaea, reshaping the microbial community. Lastly, dredging was found to promote a significant shift in functional contributions, with increases in the abundance of key enzyme activities (1.7.5.1 and 1.7.2.5) and denitrification genes (nirK, norB, and nosZ). This enhancement notably promoted denitrification and dissimilatory nitrate reduction to ammonium (DNRA), accompanied by significant environmental changes in sediment and river water. These changes facilitated the removal of nitrates in the Xiangshuitan watershed. Our study overcomes the limitations associated with watershed and microenvironment scales, providing insights into the mechanisms where by dredging activities influence the interplay between external and internal N transformations.

Mid-term Survivorship and Functional Outcomes of Metaphyseal Sleeves for Addressing Anderson Orthopaedic Research Institute (AORI) Type 2 and 3 Bone Defects in Revision Total Knee Arthroplasty.

Introduction Revision Total Knee Arthroplasty (RTKA) is a complex procedure challenged by significant bone loss, necessitating effective restoration techniques. This study investigates the clinical outcomes and complications of metaphyseal sleeves in RTKA with severe metaphyseal bone loss, aiming to evaluate their efficacy over a minimum four-year follow-up. Methods This was a retrospective observational study on 29 patients who underwent RTKA with Anderson Orthopaedic Research Institute (AORI) type II or III bone defects using porous coated tibial and/or femoral metaphyseal sleeves from December 2016 and January 2019. Data collection included demographic information, etiology for revision, and functional outcomes assessed by the Knee Society Score (KSS) and Oxford Knee Score (OKS). Statistical analysis and Kaplan-Meier survival analysis were performed. Results The cohort comprised patients with a mean age of 62.6 years (SD=7.8), predominantly female (N=21, 71.4%). The primary indication for RTKA was aseptic loosening (N=18, 62.1%) followed by Prosthetic Joint Infection (PJI). Significant improvements were noted in the range of motion. Both KSS (Pre-op:57.97 vs. Post-op:73.59) and OKS (Pre-op:15.86 vs. Post-op:30.66) showed highly significant improvement (p<0.0001). Radiographic assessments indicated stable component position and signs of osseous integration without any osteolysis. No sleeve-related complications were observed. Survival analysis demonstrated a high cumulative survival probability over the study period. Conclusion Metaphyseal sleeves offer a viable solution for managing severe bone loss in RTKA, providing stable fixation, restoring joint line kinematics, and facilitating stress distribution to the metaphyseal region. This study corroborates the effectiveness of metaphyseal sleeves in challenging revision scenarios, aligning with previous research.

Contribution of Climatic Change and Human Activities to Vegetation Dynamics over Southwest China during 2000–2020

Southwest China is an important carbon sink area in China. It is critical to track and assess how human activity (HA) and climate change (CC) affect plant alterations in order to create effective and sustainable vegetation restoration techniques. This study used MODIS NDVI data, vegetation type data, and meteorological data to examine the regional and temporal variations in the normalized difference vegetation index (NDVI) in Southwest China from 2000 to 2020. Using trend analysis, the study looks at the temporal and geographical variability in the NDVI. Partial correlation analysis was also used to assess the effects of precipitation, extreme climate indicators, and mean temperature on the dynamics of the vegetation. A new residual analysis technique was created to categorize the effects of CC and HA on NDVI changes while taking extreme climate into consideration. The findings showed that the NDVI in Southwest China grew at a rate of 0.02 per decade between 2000 and 2020. According to the annual NDVI, there was a regional rise in around 85.59% of the vegetative areas, with notable increases in 36.34% of these regions. Temperature had a major influence on the northern half of the research region, but precipitation and extreme climate had a notable effect on the southern half. The rates at which climatic variables and human activity contributed to changes in the NDVI were 0.0008/10a and 0.0034/10a, respectively. These rates accounted for 19.1% and 80.9% of the variances, respectively. The findings demonstrate that most areas displayed greater HA-induced NDVI increases, with the exception of the western Sichuan Plateau. This result suggests that when formulating vegetation restoration and conservation strategies, special attention should be paid to the impact of human activities on vegetation to ensure the sustainable development of ecosystems.

ACL reconstruction demonstrates better stability compared to ACL repair for patients with Schenck III and IV knee dislocations.

This study compared mid-term outcomes of two anterior cruciate ligament (ACL) restoration techniques within an early total surgical care of acute knee dislocation: repair with additional internal bracing (ACLIB) and reconstruction with autograft (ACLR). Initial results at 12 months demonstrated that ACLR offered superior stability compared to ACLIB. Retrospective clinical study of patients with acute type III or IV KD. ACLIB or ACLR procedures were performed accompanied by simultaneous suture and internal bracing of the posterior cruciate ligament (PCL) and repair with lateral augmentation of the medial and lateral complex injuries utilizing Arciero's reconstruction technique. Patient-reported outcome measurements (PROMs), instrumental stability assessment via the Rolimeter-Test, and stress radiographs were analyzed. The study involved 20 patients (5 IIIM, 5 IIIL, and 10 IV injuries) with an average follow-up of 35.2 ± 7.4 months. Notable differences in anterior tibial translation on stress radiography favouring ACLR persisted at 24-month follow-up in side-to-side difference (SSD) (ACLIB 2.8 ± 2.5mm vs. ACLR 0.3 ± 2.6mm; p = 0.0487), but Rolimeter test variance diminished (SSD ACLIB 2.5 ± 0.9mm vs. ACLR 1.8 ± 1.7mm). Both groups showed excellent PROMs (Lysholm Score: ACLIB 84.4 ± 15.8 vs. ACLR 89.9 ± 9.0; IKDC Score: ACLIB 77.1 ± 16.2 vs. ACLR 77.7 ± 8.6). Our results indicate improved anterior stability at 12 months, which persisted at 24 months after ACL reconstruction compared with ACL repair by stress radiography. Both groups showed favourable patient-reported outcomes throughout the follow-up period. Notable rates of postoperative knee stiffness were observed in both groups. These were successfully managed with early, one-time arthroscopic arthrolysis within the first seven months of treatment, resulting in no major range of motion limitations at the 24-month follow-up. Retrospective cohort study, III.

Underwater image restoration method based on Walsh–Hadamard transform and attenuation coefficient estimation

Abstract Underwater images often exhibit color distortion and low contrast due to the scattering and absorption of light as it travels through water. Changes in lighting conditions further complicate the restoration and enhancement of these images. Improving the quality of underwater images is crucial for advancements in fields such as marine biology research, underwater measurement, and environmental monitoring. This paper proposes an underwater image restoration method based on the Image Formation Model (IFM), utilizing the Walsh–Hadamard transform and attenuation coefficient estimation. Traditional methods rely on dark channel prior and maximum intensity prior to estimate background light (BL) and transmission maps (TMs), often performing poorly in various underwater environments. Our method uses image blur to estimate BL and depth maps and derives three-channel attenuation coefficients using the gray-world theory to obtain a more accurate TM. Experimental results on real underwater images show that our method effectively eliminates color deviation and contrast distortion while preserving image details, significantly outperforming other IFM-based restoration techniques. Compared to the closest competing algorithms, our method achieves better UIQM and UCIQE scores.

Alzheimer’s Disease: An Outline of Therapeutic Interventions by different Approaches

A neurodegenerative condition called Alzheimer's disease (AD) impairs neurocognitive function and hinders the growth of mental ability. This neuropathological condition presents with neurodegeneration, neuronal loss, and the development of neurofibrillary tangles and Ab plaques. Dementia, neuronal loss, and the development of neurofibrillary tangles and Ab plaques are the hallmarks of this neuropathological disorder. Such a medication is not able to cure Alzheimer's disease. The drug that's now available just treats symptoms. Two major obstacles to research are the blood-brain barrier, which reduces the effectiveness of treatments, and the incomplete comprehension of the ethology of Alzheimer's disease. Stem cell-based therapy has been seen as a novel, reliable and successful restoration technique to treat AD since the condition is complex and has not gotten much attention. The latest advances in nanotechnology occasionally offer proactive treatment chances that can help get over limitations. In this overview, we concentrate on the causes of AD and the various methods used to treat them.

Water damage restoration, structural drying and remediation of damp issues in UK properties : A comprehensive review

Water damage is a pervasive issue in the UK, with adverse effects on property structures and indoor air quality. This paper provides a comprehensive review of water damage restoration, structural drying and remediation techniques tailored to UK properties. It discusses the causes of water damage, including flooding, leaks and dampness, and explores the principles and methods of effective restoration and remediation. Special attention is given to the unique challenges and considerations faced by property owners, contractors and restoration professionals in the UK context.

In Vitro Study Of Molar Tooth With Endodontic Treatment At Endocrown Successful Prosthetic Rehabilitation

Background: Side teeth, having a decisive role for mastication, require special attention after endodontic treatment. The rehabilitation of these teeth includes the analysis of current restoration techniques, materials used, as well as aesthetic and functional impact on the patient. Through a multidisciplinary approach, it aims not only to recover dental function, but also to improve the quality of life of the patient by restoring a healthy and harmonious smile. Materials and Methods: In this study, we conducted tests on 30 extracted teeth that had whole or partially whole dental crowns, the condition of selecting the tooth in the study being at least 3 mm of dental tissue present, and, necessary for the subsequent prosthetic preparation for endocrown prosthetics. The 30 teeth were divided into 6 batches, the control group (A) being made up only of integral teeth that were milling for covering crowns. The other teeth were divided into 5 batches (B-F) of 5 teeth, the teeth were endodontically treated and milling for prosthetic rehabilitation with endocrown. Each lot (B-F) benefited from a preparation of coronoradicular cylindrical shape of different depths between 0.5-2,5mm, on the occlusal face of the tooth in the endodontic access area, in order to increase the surface of the retention coronary dental tissues for the stability of the prosthetic crowns of the coating. Each tooth in A-F batches has benefited from 3 crowns made of the same material through 3 different technologies. Results: The values recorded by the A-lot, rehabilitated with crowns of sheathing on integral teeth, recorded an average value of the crown extraction force on tooth of 25.42±0.55 for CAD-CAM technology, for crowns made by baro-thermo-polymerization technique an average of 24,14±0,37, and for hot polymerization technique an average of 23,66±0,37. For B-F batches, the closest values for the extraction of endocorons were obtained by lot D with a preparation in the corono-radicular axe of 1,5mm, both for the CAD-CAM technology with a average of 25,74±1,91, and for the technique baro-thermo polymerization with an average of 24,92±1,83. For the technique of hot polymerization batch E, who has a preparation of 2 mm in the corono-radicular axe, recording an average of the extraction force of the endocrown of 23.56±2.05. Conclusion: The success of endodontic treatment also depends on prosthetic restoration for a long-term oral rehabilitation

Dual Stage Bionic Spatial Convolutional Restoration Model for Image De-noising and De-mosaicking

The first two important steps in the pipeline for processing picture signals are de-noising and de-mosaicking. The joint solution of the highly uncertain inverse problem of de-noising and de-mosaicking has garnered increased attention in research today. It is difficult to restore high-quality images from raw data in low light because of a variety of disturbances brought on by a low photon count and a complex image signal processing scheme. Even if some restoration and improvement techniques have been used, they might not work in harsh situations, including raw data imaging with brief exposure. Therefore, this research focuses on developing a de-mosaicking and de-noising model with effective end to end manner outcomes. Initially, the pre-processing is conducted using Gaussian filtering to eliminate artifacts from the input image, thereby enhancing the image quality. Then, the proposed method incorporates an Enhanced Spatial Convolutional Residual Net (EnConvResNet) for image de-mosaicking and an Adaptive U-net restoration model for image de-noising. An enhanced gazelle optimization (EnGa) algorithm is used to fine-tune the hyper-parameters of the model in order to maximize its performance and improve its generalization capacity. The proposed method accomplished peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM) of 46.65 and 98.89, respectively.

Patellar tendon restoration techniques: a systematic review of outcomes for repair and reconstruction methods.

This systematic review aims to delineate the various methods to repair or reconstruct the patellar tendon using the available literature. MEDLINE and PubMed electronic databases were searched for English language clinical studies involving patellar tendon rupture repair or reconstruction that reported patient-reported outcome scores (PROS) between January 1st, 1953 and June 17th, 2021. Data was extracted on full text articles to collect functional outcome scores and rupture category, including acute, chronic, post-total knee arthroplasty (TKA) and post-anterior cruciate ligament reconstruction (ACLR). Twenty-three studies with a total of 738 patients were included. Of the 14 studies including acute repairs, mean postoperative Lvsholm scores ranged from 84 to 99.5. Knee Society Score (KSS) and knee range of motion (ROM) measurement were the most widely reported outcomes in the chronic setting. The average postoperative KSS scores ranged from 70 to 87.7. Of the six studies that included patellar tendon repairs/reconstructions in the setting of prior TKA, the most frequently reported outcomes were KSS scores and knee ROM measurements. The average postoperative KSS scores for the three cohorts reporting reconstruction with allograft ranged from 79 to 88 as compared to the average postoperative KSS score for reconstruction with autograft of 70. Despite this heterogeneity, we concluded: (1) in the primary setting, cerclage augmentation yields the lowest lysholm scores and should not be considered, although primary repairs with and without augmentation yield comparable postoperative lysholm scores, (2) in the chronic setting, repair with augmentation and reconstruction yielded similar results aside from in post-TKA patients where allograft reconstruction yielded superior KSS scores.

AI-POWERED IMAGE ENHANCEMENT IN FORENSIC APPLICATIONS: CHALLENGES AND OPPORTUNITIES

Recent progress in machine learning (ML) and computer vision has markedly enhanced the performance of automated facial recognition systems. Nonetheless, forensic applications frequently face issues with poor-quality and low-resolution images that pose challenges even to the most advanced facial recognition technologies. This research explores the potential of neural-based image enhancement and restoration techniques to recover degraded images while maintaining original correspondences for legal use. We evaluate super-resolution and deconvolution methods across two comprehensive and varied facial datasets. Our study employs twelve distinct GAN- and diffusion-based enhancement techniques. Our results offer insights and recommendations for the effective application of image enhancement in forensic facial recognition, highlighting the advantages and potential limitations of these advanced technologies.

Gaussian second derivative blur kernels for image deblurring

Image blur is a common image degradation phenomenon that occurs in case of camera movement and lens defocusing. In order to deblur the image, point spread function (PSF) model is often used to match the real blur kernel, but currently the matching effect is poor. In this paper, an image restoration technique based on the Gaussian Second Derivative (GSD) fitted PSF is proposed to address this problem. Firstly, a GSD model is proposed. The actual image Line spread function (LSF) extracted by knife-edge method is modeled as a linear combination of a series of Gaussian second derivatives. Then, an improved annihilation filtering algorithm is proposed. The algorithm is used to estimate the parameters of the GSD model, so as to remove the errors in the actual complex scenarios. Finally, the image PSF is obtained by using the LSF curve fitted and corrected by the GSD model, and combined with the existing Richardson-Lucy (R-L) algorithm, the clear image is finally restored. Experimental results show that compared with the existing image restoration strategies based on other PSF models, this method can effectively improve the image restoration accuracy.

Restoration of fractured anterior tooth with monochrome composite resin in pediatric dental patient

Direct restoration with monochromatic composite resin is a treatment option for teeth with coronal fracture after dentoalveolar trauma. This restorative material, in principle, is capable of mimicking the color of the dental substrate. This study aimed to report and discuss the technique of direct restoration with monochromatic composite resin, in a child patient. An 8-year-old male patient attended the Emergency Room of the Baby Clinic of the State University of Londrina for immediate treatment after dentoalveolar trauma that resulted in enamel and dentin fracture, without pulp involvement. As a procedure, restoration was performed with glass ionomer cement and referral to the institution's Dental Residency program. In this service, after case planning, the restoration of the coronal fracture of the substrates was performed with the insertion of multiple increments of the Vittra APS Unique (FGM) composite, with the aid of a silicone guide prepared based on a waxing model to facilitate the reestablishment of the palatal surface form and anatomy. In the clinical follow-up evaluation, the aesthetic and functional results obtained were considered highly satisfactory by patients, relatives and dental clinicians. Thus, it can be concluded that the option for monochromatic composite resin is a viable alternative to make it easier for the dental clinicians to perform the procedure and reduce the clinical time, a relevant fact because it is a case of caring for a pediatric dentistry patient.

Pretraining of 3D image segmentation models for retinal OCT using denoising-based self-supervised learning.

Deep learning algorithms have allowed the automation of segmentation for many biomarkers in retinal OCTs, enabling comprehensive clinical research and precise patient monitoring. These segmentation algorithms predominantly rely on supervised training and specialised segmentation networks, such as U-Nets. However, they require segmentation annotations, which are challenging to collect and require specialized expertise. In this paper, we explore leveraging 3D self-supervised learning based on image restoration techniques, that allow to pretrain 3D networks with the aim of improving segmentation performance. We test two methods, based on image restoration and denoising. After pretraining on a large 3D OCT dataset, we evaluate our weights by fine-tuning them on two challenging fluid segmentation datasets utilising different amount of training data. The chosen methods are easy to set up while providing large improvements for fluid segmentation, enabling the reduction of the amount of required annotation or an increase in the performance. Overall, the best results were obtained for denoising-based SSL methods, with higher results on both fluid segmentation datasets as well as faster pretraining durations.

Adaptive and automatic aerial image restoration pipeline leveraging pre-trained image restorer with lightweight Fully Convolutional Network

Earth observation and remote sensing necessitate the use of aerial imaging, and unmanned aerial vehicles (UAVs) are widely utilized for this purpose. Although UAVs can be costly, using inexpensive components could result in issues such as noise, defocusing, and motion blur. Utilizing advanced deep learning algorithms, these images can be effectively restored. However, this necessitates the use of physical effort since each image must be restored manually. Our work introduces a new pipeline that can automatically categorize the degradation types of aerial images and subsequently apply the necessary restoration techniques on degraded images. A lightweight adaptive degradation classifier model was proposed to handle input from images of varying sizes and provide guidance to a image restoration model for achieving the desired task. The degradation classifier is a Fully Convolutional Network capable of categorizing images of any size into 3 distinct classes. It offers guidance to the subsequent image restorer. The restoration model is a pre-trained transformer-based model that efficiently restores different types of image degradations. In addition, we have implemented a pipeline loss to assess the performance of our complete system. To build the system, a dataset is created by extracting cropped patches from high-resolution images obtained through Google Earth. Subsequently, the clean patches were artificially deteriorated by applying different filters to replicate the image degradations. The degradation classifier achieved a mean accuracy of 96.71% across 6 different test scenarios, with a standard deviation of 2.97. The mean pipeline loss was 24.95, with a standard deviation of 1.79. Furthermore, we showcased the efficacy of our pipeline in a practical implementation involving aerial imagery, specifically in the domain of vehicle detection. We conducted training on an object detection model and then evaluated the detection performance on both degraded and automatically restored images. Our experiments demonstrate the efficient performance of our method in automatically restoring degraded aerial images, even though the restoration models were not specifically trained on aerial images. In addition, we examined current limitations and difficulties in creating such systems and offered comprehensive perspectives on future advancements.

Investigation of Different Generative Adversarial Networks Techniques for Image Restoration

Investigation of Different Generative Adversarial Networks Techniques for Image Restoration

Underwater image restoration based on light attenuation prior and color-contrast adaptive correction

Underwater imaging is uniquely beset by issues such as color distortion and diminished contrast due to the intricate behavior of light as it traverses water, being attenuated by processes of absorption and scattering. Distinct from traditional underwater image restoration techniques, our methodology uniquely accommodates attenuation coefficients pertinent to diverse water conditions. We endeavor to recover the pristine image by approximating decay rates, focusing particularly on the blue-red and blue-green color channels. Recognizing the inherent ambiguities surrounding water type classifications, we meticulously assess attenuation coefficient ratios for an array of predefined aquatic categories. Each classification results in a uniquely restored image, and an automated selection algorithm is employed to determine the most optimal output, rooted in its color distribution. In tandem, we've innovated a color-contrast adaptive correction technique, purposefully crafted to remedy color anomalies in underwater images while simultaneously amplifying contrast and detail fidelity. Extensive trials on benchmark datasets unambiguously highlight our method's preeminence over six other renowned strategies. Impressively, our methodology exhibits exceptional resilience and adaptability, particularly in scenarios dominated by green background imagery.

Research on deep learning restoration algorithm of X-ray backscatter imaging based on virtual training dataset

The X-ray lobster eye lens, an innovative technique for focusing high-energy radiation, enables wide-field X-ray imaging. However, its inherent cross point spread function introduces noise and degradation into the resultant images. Conventional image restoration methods are inadequate for suppressing such noise. This paper introduces a backscatter image restoration technique utilizing a virtual training dataset. By convolving the point spread function (PSF) with an object to simulate the image degradation process, the method generates a multitude of convolved images for deep learning training, eliminating the need for manual annotation. Given the high structural similarity between the synthetic convolved images and actual backscatter images, the trained model effectively restores real backscatter images. The restoration process yields a structural similarity index (SSIM) of 0.86 and a mean intersection over union (MIoU) of 0.83 when compared to the reference images. This approach mitigates the limitations of sparse real backscatter datasets, substantially reducing image acquisition time, decreasing radiation flux, and enhancing system safety.

New Guidelines for the Treatment of the Alveolar Septum in Immediate Dentoalveolar Restoration Technique Associated with Osseodensification: A Case Series.

Achieving initial implant stability at the molar extraction site can be challenging due to bone width, quality, and anatomical limitations like the maxillary sinus and inferior alveolar nerve. The implant placement should achieve precise centralization with the interradicular septum to facilitate implant stabilization and preservation/regeneration of the alveolar ridge post-extraction with bone grafting. Immediate non-occlusal crown placement aids peri-implant tissue maturation for the desired outcome. This retrospective series introduces guidelines for treating sockets with alveolar septum types. The approach involves immediate dentoalveolar restoration (IDR) and osseodensification (OD) with an autogenous graft for bone preservation. A new protocol for the treatment of the molar interradicular septum during immediate implant placement and/or alveolar ridge preservation/reconstruction was applied in 12 cases. Preoperative and postoperative cone-beam computed tomographic examinations were performed. Socket width was measured and compared between timepoints. The mean preoperative and postoperative (mean, 23.58 ± 9.70 months) socket widths were 9.51 ± 0.40 and 11.16 ± 0.30 mm, respectively (17.35% increase; p <0.05). IDR with OD is a predictable approach to the treatment of molar sockets during implant placement.