Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 30.225
Filtrar
1.
Sci Rep ; 12(1): 15131, 2022 Sep 06.
Artigo em Inglês | MEDLINE | ID: mdl-36068281

RESUMO

The pressure reactivity index (PRx) is a parameter for the assessment of cerebrovascular autoregulation, but its calculation is affected by artifacts in the source biosignals-intracranial pressure (ICP) and arterial blood pressure. We sought to describe the most common short-duration artifacts and their effect on the PRx. A retrospective analysis of 935 h of multimodal monitoring data was conducted, and five types of artifacts, characterized by their shape, duration, and amplitude, were identified: rectangular, fast impulse, isoline drift, saw tooth, and constant ICP value. Subsequently, all types of artifacts were mathematically modeled and inserted into undisturbed segments of biosignals. Fast impulse, the most common artifact, did not alter the PRx index significantly when inserted into one or both signals. Artifacts present in one signal exceeded the threshold PRx in less than 5% of samples, except for isoline drift. Compared to that, the shortest rectangular artifact inserted into both signals changed PRx to a value above the set threshold in 55.4% of cases. Our analysis shows that the effect of individual artifacts on the PRx index is variable, depending on their occurrence in one or both signals, duration, and shape. This different effect suggests that potentially not all artifacts need to be removed.


Assuntos
Artefatos , Lesões Encefálicas Traumáticas , Pressão Arterial/fisiologia , Circulação Cerebrovascular/fisiologia , Humanos , Pressão Intracraniana/fisiologia , Estudos Retrospectivos
2.
Med Oncol ; 39(12): 198, 2022 Sep 07.
Artigo em Inglês | MEDLINE | ID: mdl-36071299

RESUMO

Cancer has become the silent killer in less-developed countries and the most significant cause of morbidity worldwide. The accessible and frequently used treatments include surgery, radiotherapy, chemotherapy, and immunotherapy. Chemotherapeutic drugs traditionally involve using plant-based medications either in the form of isolated compounds or as scaffolds for synthetic drugs. To launch a drug in the market, it has to pass through several intricate steps. The multidrug resistance in cancers calls for novel drug discovery and development. Every year anticancer potential of several plant-based compounds and extracts is reported but only a few advances to clinical trials. The false-positive or negative results impact the progress of the cell-based anticancer assays. There are several cell-based assays but the widely used include MTT, MTS, and XTT. In this article, we have discussed various pitfalls and workable solutions.


Assuntos
Colorimetria , Neoplasias , Artefatos , Desenvolvimento de Medicamentos , Descoberta de Drogas , Humanos , Neoplasias/tratamento farmacológico
3.
Sci Rep ; 12(1): 14947, 2022 Sep 02.
Artigo em Inglês | MEDLINE | ID: mdl-36056042

RESUMO

Level set models are suitable for processing topological changes in different regions of images while performing segmentation. Active contour models require an empirical setting for initial parameters, which is tedious for the end-user. This study proposes an incremental level set model with the automatic initialization of contours based on local and global fitting energies that enable it to capture image regions containing intensity corruption or other light artifacts. The region-based area and the region-based length terms use signed pressure force (SPF) to strengthen the balloon force. SPF helps to achieve a smooth version of the gradient descent flow in terms of energy minimization. The proposed model is tested on multiple synthetic and real images. Our model has four advantages: first, there is no need for the end user to initialize the parameters; instead, the model is self-initialized. Second, it is more accurate than other methods. Third, it shows lower computational complexity. Fourth, it does not depend on the starting position of the contour. Finally, we evaluated the performance of our model on microscopic cell images (Coelho et al., in: 2009 IEEE international symposium on biomedical imaging: from nano to macro, IEEE, 2009) to confirm that its performance is superior to that of other state-of-the-art models.


Assuntos
Algoritmos , Processamento de Imagem Assistida por Computador , Artefatos , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos
4.
J Acoust Soc Am ; 152(2): 921, 2022 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-36050163

RESUMO

In this paper, we propose a dual projection generalized sidelobe canceller (DPGSC) based on mixed subspace (MS) for ultrasound imaging, which aims to improve the speckle signal-noise-ratio (sSNR) and decrease the dark-region artifacts. A mixed signal subspace based on the correlation between the desired steering vector and the eigenvectors is constructed to further optimize the desired steering vector and the final weight vector. The simulated and experimental results show that the proposed method can greatly improve the speckle uniformity. In the geabr_0 experiment, the standard deviation of background and sSNR of MS-DPGSC can be improved by 48.07% and 58.49% more than those of eigenspace-based generalized sidelobe canceller (ESGSC). Furthermore, for a hyperechoic target, the maximal improvement of contrast ratio is 95.29%. In terms of anechoic cyst, the contrast-to-noise ratio of MS-DPGSC is increased by 123.08% than that of ESGSC. The rat mammary tumor experimental data show that the proposed method has better comprehensive imaging effect than traditional generalized sidelobe cancellers and ESGSCs.


Assuntos
Algoritmos , Artefatos , Animais , Imagens de Fantasmas , Ratos , Razão Sinal-Ruído , Ultrassonografia/métodos
5.
Sensors (Basel) ; 22(17)2022 Aug 23.
Artigo em Inglês | MEDLINE | ID: mdl-36080793

RESUMO

The analysis and segmentation of articular cartilage magnetic resonance (MR) images belongs to one of the most commonly routine tasks in diagnostics of the musculoskeletal system of the knee area. Conventional regional segmentation methods, which are based either on the histogram partitioning (e.g., Otsu method) or clustering methods (e.g., K-means), have been frequently used for the task of regional segmentation. Such methods are well known as fast and well working in the environment, where cartilage image features are reliably recognizable. The well-known fact is that the performance of these methods is prone to the image noise and artefacts. In this context, regional segmentation strategies, driven by either genetic algorithms or selected evolutionary computing strategies, have the potential to overcome these traditional methods such as Otsu thresholding or K-means in the context of their performance. These optimization strategies consecutively generate a pyramid of a possible set of histogram thresholds, of which the quality is evaluated by using the fitness function based on Kapur's entropy maximization to find the most optimal combination of thresholds for articular cartilage segmentation. On the other hand, such optimization strategies are often computationally demanding, which is a limitation of using such methods for a stack of MR images. In this study, we publish a comprehensive analysis of the optimization methods based on fuzzy soft segmentation, driven by artificial bee colony (ABC), particle swarm optimization (PSO), Darwinian particle swarm optimization (DPSO), and a genetic algorithm for an optimal thresholding selection against the routine segmentations Otsu and K-means for analysis and the features extraction of articular cartilage from MR images. This study objectively analyzes the performance of the segmentation strategies upon variable noise with dynamic intensities to report a segmentation's robustness in various image conditions for a various number of segmentation classes (4, 7, and 10), cartilage features (area, perimeter, and skeleton) extraction preciseness against the routine segmentation strategies, and lastly the computing time, which represents an important factor of segmentation performance. We use the same settings on individual optimization strategies: 100 iterations and 50 population. This study suggests that the combination of fuzzy thresholding with an ABC algorithm gives the best performance in the comparison with other methods as from the view of the segmentation influence of additive dynamic noise influence, also for cartilage features extraction. On the other hand, using genetic algorithms for cartilage segmentation in some cases does not give a good performance. In most cases, the analyzed optimization strategies significantly overcome the routine segmentation methods except for the computing time, which is normally lower for the routine algorithms. We also publish statistical tests of significance, showing differences in the performance of individual optimization strategies against Otsu and K-means method. Lastly, as a part of this study, we publish a software environment, integrating all the methods from this study.


Assuntos
Cartilagem Articular , Algoritmos , Artefatos , Cartilagem Articular/diagnóstico por imagem , Análise por Conglomerados , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos
6.
Sensors (Basel) ; 22(17)2022 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-36080849

RESUMO

The purpose of infrared and visible image fusion is to generate images with prominent targets and rich information which provides the basis for target detection and recognition. Among the existing image fusion methods, the traditional method is easy to produce artifacts, and the information of the visible target and texture details are not fully preserved, especially for the image fusion under dark scenes and smoke conditions. Therefore, an infrared and visible image fusion method is proposed based on visual saliency image and image contrast enhancement processing. Aiming at the problem that low image contrast brings difficulty to fusion, an improved gamma correction and local mean method is used to enhance the input image contrast. To suppress artifacts that are prone to occur in the process of image fusion, a differential rolling guidance filter (DRGF) method is adopted to decompose the input image into the basic layer and the detail layer. Compared with the traditional multi-scale decomposition method, this method can retain specific edge information and reduce the occurrence of artifacts. In order to solve the problem that the salient object of the fused image is not prominent and the texture detail information is not fully preserved, the salient map extraction method is used to extract the infrared image salient map to guide the fusion image target weight, and on the other hand, it is used to control the fusion weight of the basic layer to improve the shortcomings of the traditional 'average' fusion method to weaken the contrast information. In addition, a method based on pixel intensity and gradient is proposed to fuse the detail layer and retain the edge and detail information to the greatest extent. Experimental results show that the proposed method is superior to other fusion algorithms in both subjective and objective aspects.


Assuntos
Algoritmos , Aumento da Imagem , Artefatos , Aumento da Imagem/métodos , Processamento de Imagem Assistida por Computador/métodos
7.
Sensors (Basel) ; 22(17)2022 Aug 27.
Artigo em Inglês | MEDLINE | ID: mdl-36080918

RESUMO

Three-dimensional mesh post-processing is an important task because low-precision hardware and a poor capture environment will inevitably lead to unordered point clouds with unwanted noise and holes that should be suitably corrected while preserving the original shapes and details. Although many 3D mesh data-processing approaches have been proposed over several decades, the resulting 3D mesh often has artifacts that must be removed and loses important original details that should otherwise be maintained. To address these issues, we propose a novel 3D mesh completion and denoising system with a deep learning framework that reconstructs a high-quality mesh structure from input mesh data with several holes and various types of noise. We build upon SpiralNet by using a variational deep autoencoder with anisotropic filters that apply different convolutional filters to each vertex of the 3D mesh. Experimental results show that the proposed method enhances the reconstruction quality and achieves better accuracy compared to previous neural network systems.


Assuntos
Artefatos , Redes Neurais de Computação , Anisotropia , Cabeça
8.
Sensors (Basel) ; 22(17)2022 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-36081157

RESUMO

With the development of portable EEG acquisition systems, the collected EEG has gradually changed from being multi-channel to few-channel or single-channel, thus the removal of single-channel EEG signal artifacts is extremely significant. For the artifact removal of single-channel EEG signals, the current mainstream method is generally a combination of the decomposition method and the blind source separation (BSS) method. Between them, a combination of empirical mode decomposition (EMD) and its derivative methods and ICA has been used in single-channel EEG artifact removal. However, EMD is prone to modal mixing and it has no relevant theoretical basis, thus it is not as good as variational modal decomposition (VMD) in terms of the decomposition effect. In the ICA algorithm, the implementation method based on high-order statistics is widely used, but it is not as effective as the implementation method based on second order statistics in processing EMG artifacts. Therefore, aiming at the main artifacts in single-channel EEG signals, including EOG and EMG artifacts, this paper proposed a method of artifact removal combining variational mode decomposition (VMD) and second order blind identification (SOBI). Semi-simulation experiments show that, compared with the existing EEMD-SOBI method, this method has a better removal effect on EOG and EMG artifacts, and can preserve useful information to the greatest extent.


Assuntos
Artefatos , Processamento de Sinais Assistido por Computador , Algoritmos , Simulação por Computador , Eletroencefalografia/métodos
9.
IEEE Trans Image Process ; 31: 5774-5787, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36048976

RESUMO

The major challenge in high dynamic range (HDR) imaging for dynamic scenes is suppressing ghosting artifacts caused by large object motions or poor exposures. Whereas recent deep learning-based approaches have shown significant synthesis performance, interpretation and analysis of their behaviors are difficult and their performance is affected by the diversity of training data. In contrast, traditional model-based approaches yield inferior synthesis performance to learning-based algorithms despite their theoretical thoroughness. In this paper, we propose an algorithm unrolling approach to ghost-free HDR image synthesis algorithm that unrolls an iterative low-rank tensor completion algorithm into deep neural networks to take advantage of the merits of both learning- and model-based approaches while overcoming their weaknesses. First, we formulate ghost-free HDR image synthesis as a low-rank tensor completion problem by assuming the low-rank structure of the tensor constructed from low dynamic range (LDR) images and linear dependency among LDR images. We also define two regularization functions to compensate for modeling inaccuracy by extracting hidden model information. Then, we solve the problem efficiently using an iterative optimization algorithm by reformulating it into a series of subproblems. Finally, we unroll the iterative algorithm into a series of blocks corresponding to each iteration, in which the optimization variables are updated by rigorous closed-form solutions and the regularizers are updated by learned deep neural networks. Experimental results on different datasets show that the proposed algorithm provides better HDR image synthesis performance with superior robustness compared with state-of-the-art algorithms, while using significantly fewer training samples.


Assuntos
Algoritmos , Artefatos , Diagnóstico por Imagem , Movimento (Física) , Redes Neurais de Computação
10.
BMC Med Imaging ; 22(1): 156, 2022 09 03.
Artigo em Inglês | MEDLINE | ID: mdl-36057551

RESUMO

BACKGROUND: This study aimed to compare the amount of artifacts induced by the titanium and zirconium implants on cone-beam computed tomography (CBCT) and assess the effect of different exposure settings on the image quality for both materials. METHODS: In this experimental study, 30 zirconium and 30 titanium implants were placed in bovine rib bone blocks. CBCT images were taken in two different fields of view (FOV: 4 × 6 cm2 and 6 × 8 cm2) and at two resolutions (133 µ and 200 µ voxel size). Subsequently, two observers assessed the images and detected the amount of artifacts around the implants through gray values. Data were analyzed by paired t test and independent t test using SPSS 21 and the 0.05 significance level. RESULTS: The results showed that titanium implants caused lower amounts of artifacts than zirconium implants, which was statistically significant (P < 0.001). The larger FOV (6 × 8 cm2) resulted in a lower amount of artifacts in both groups, although the results were only statistically significant in the zirconium group (P < 0.001). The amount of artifacts was increased when using the 133 µ voxel size in both groups, which was only significant in the zirconium group (P < 0.001). CONCLUSION: Our results suggest that zirconium implants induce higher amounts of artifacts than titanium ones. We also concluded that the artifacts could be minimized using the larger FOV and voxel size.


Assuntos
Artefatos , Zircônio , Animais , Bovinos , Tomografia Computadorizada de Feixe Cônico/métodos , Humanos , Titânio
11.
BMC Med Imaging ; 22(1): 161, 2022 09 06.
Artigo em Inglês | MEDLINE | ID: mdl-36068498

RESUMO

BACKGROUND: Patients with tonsillar cancer (TC) often have dental fillings that can significantly degrade the quality of computed tomography (CT) simulator images due to metal artifacts. We evaluated whether the use of the metal artifact reduction (MAR) algorithm reduced the interobserver variation in delineating gross tumor volume (GTV) of TC. METHODS: Eighteen patients with TC with dental fillings were enrolled in this study. Contrast-enhanced CT simulator images were reconstructed using the conventional (CTCONV) and MAR algorithm (CTMAR). Four board-certified radiation oncologists delineated the GTV of primary tumors using routine clinical data first on CTCONV image datasets (GTVCONV), followed by CTCONV and CTMAR fused image datasets (GTVMAR) at least 2 weeks apart. Intermodality differences in GTV values and Dice similarity coefficient (DSC) were compared using Wilcoxon's signed-rank test. RESULTS: GTVMAR was significantly smaller than GTVCONV for three observers. The other observer showed no significant difference between GTVCONV and GTVMAR values. For all four observers, the mean GTVCONV and GTVMAR values were 14.0 (standard deviation [SD]: 7.4) cm3 and 12.1 (SD: 6.4) cm3, respectively, with the latter significantly lower than the former (p < 0.001). The mean DSC of GTVCONV and GTVMAR was 0.74 (SD: 0.10) and 0.77 (SD: 0.10), respectively, with the latter significantly higher than that of the former (p < 0.001). CONCLUSIONS: The use of the MAR algorithm led to the delineation of smaller GTVs and reduced interobserver variations in delineating GTV of the primary tumors in patients with TC.


Assuntos
Neoplasias Tonsilares , Algoritmos , Artefatos , Humanos , Variações Dependentes do Observador , Planejamento da Radioterapia Assistida por Computador/métodos , Neoplasias Tonsilares/diagnóstico por imagem , Carga Tumoral
12.
J Obstet Gynaecol Can ; 44(9): 1016-1027.e1, 2022 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-36109100

RESUMO

OBJECTIVE: To improve perinatal outcomes and minimize provider error by increasing awareness of strategies to detect intrapartum maternal heart rate artefact and to respond when such artefact is suspected. TARGET POPULATION: All pregnant patients during labour. OPTIONS: Maternal heart rate artefact may be detected based on clinical features or through technology. Suspected maternal heart rate artefact may be assessed by applying a fetal scalp electrode (preferred) or through external fetal monitoring, augmented by point-of-care sonography (alternative). OUTCOMES: Unrecognized intrapartum maternal heart rate artefact increases the risk that abnormal/atypical fetal heart rate patterns will go undetected and, hence, the risk of adverse perinatal outcomes. BENEFITS, HARMS, AND COSTS: Unrecognized maternal heart rate artefact can lead to adverse perinatal outcomes (hypoxic-ischemic encephalopathy, fetal death, and neonatal death) and adverse maternal outcomes (unnecessary cesarean delivery or operative vaginal delivery). Timely recognition of such artefact may avoid these adverse outcomes. The costs of early recognition of maternal heart rate artefact are relatively small: increased use of fetal scalp electrodes and point-of-care sonography, as well as additional assessments by the health care provider. The cost savings are significant, as a result of lower risk of adverse perinatal outcomes. Potential harms are false-positive diagnoses of maternal heart rate artefact, expediting delivery unnecessarily when the fetal status cannot be reliably determined but is normal, and the rare complications associated with increased use of fetal scalp electrodes. EVIDENCE: Two PubMed searches were completed. The first was for articles published between January 1, 1970, and November 25, 2021, using the medical subject headings (MeSH) "fetal monitoring" and "artifacts" (38 articles). The second was for articles published during the same period using the MeSH "fetal monitoring" and "maternal heart rate" (841 articles). VALIDATION METHODS: The authors rated the quality of evidence and strength of recommendations using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. See online Appendix A (Tables A1 for definitions and A2 for interpretations of strong and conditional [weak] recommendations). INTENDED AUDIENCE: All health care providers involved in obstetrical care. SUMMARY STATEMENTS: RECOMMENDATIONS.


Assuntos
Artefatos , Monitorização Fetal , Cardiotocografia , Feminino , Frequência Cardíaca Fetal/fisiologia , Humanos , Recém-Nascido , Gravidez , Cuidado Pré-Natal
13.
J Obstet Gynaecol Can ; 44(9): 1028-1039.e1, 2022 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-36109101

RESUMO

OBJECTIF: Améliorer les issues périnatales et réduire au minimum le risque d'erreurs chez les fournisseurs en améliorant leurs connaissances sur les stratégies de détection des artéfacts de la fréquence cardiaque maternelle per partum et sur les modes d'intervention lorsque de tels artéfacts sont soupçonnés. POPULATION CIBLE: Toutes les parturientes. OPTIONS: L'artéfact de la fréquence cardiaque maternelle peut être détecté à l'aide de caractéristiques cliniques ou de la technologie. On peut évaluer l'artéfact de la fréquence cardiaque maternelle soupçonné en posant une électrode de cuir chevelu fœtal (option à privilégier) ou en recourant à la surveillance fœtale externe optimisée par l'échographie au chevet (solution de rechange). RéSULTATS: Les artéfacts de la fréquence cardiaque maternelle per partum non détectés augmentent le risque que des rythmes anormaux ou atypiques de la fréquence cardiaque fœtale passent inaperçus, ce qui augmente le risque d'issues périnatales défavorables. BéNéFICES, RISQUES ET COûTS: L'artéfact de la fréquence cardiaque maternelle non détecté peut entraîner de graves issues périnatales défavorables (encéphalopathie hypoxo-ischémique, mort fœtale et mort néonatale) et des issues maternelles défavorables (césarienne injustifiée ou accouchement assisté). Ces issues peuvent être évitées par la détection rapide d'un tel artéfact. Le coût de la détection précoce des artéfacts de fréquence cardiaque maternelle est relativement faible (utilisation accrue des électrodes de cuir chevelu fœtal et de l'échographie au chevet avec évaluations supplémentaires par le fournisseur de soins). La réduction des événements périnataux défavorables engendre des économies considérables. Les risques sont : faux positifs d'artéfact de la fréquence cardiaque maternelle; accélération inutile de l'accouchement lorsque l'état du fœtus est normal, mais qu'on ne peut le déterminer de façon fiable; et les rares complications associées à l'utilisation accrue des électrodes de cuir chevelu fœtal. DONNéES PROBANTES: Deux recherches ont été effectuées dans PubMed. La première a été réalisée pour répertorier les articles publiés entre le 1er janvier 1970 et le 25 novembre 2021 à partir des termes MeSH fetal monitoring et artifacts (38 articles); la deuxième, pour répertorier les articles publiés au cours de la même période à partir des termes MeSH fetal monitoring et maternal heart rate (841 articles). MéTHODES DE VALIDATION: Les auteurs ont évalué la qualité des données probantes et la force des recommandations en utilisant le cadre méthodologique GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Voir l'annexe A en ligne (tableau A1 pour les définitions et tableau A2 pour l'interprétation des recommandations fortes et conditionnelles [faibles]). PROFESSIONNELS CONCERNéS: Tous les fournisseurs de soins obstétricaux. DÉCLARATIONS SOMMAIRES: RECOMMANDATIONS.


Assuntos
Artefatos , Feto , Feminino , Humanos , Gravidez
14.
Sci Rep ; 12(1): 15549, 2022 Sep 16.
Artigo em Inglês | MEDLINE | ID: mdl-36114270

RESUMO

Cone-beam computed tomography (CBCT) has been shown to be a powerful tool for 3D imaging of the appendicular skeleton, allowing for detailed visualization of bone microarchitecture. This study was designed to compare artifacts in the presence of osteosynthetic implants between CBCT and multidetector computed tomography (MDCT) in cadaveric wrist scans. A total of 32 scan protocols with varying tube potential and current were employed: both conventional CBCT and MDCT studies were included with tube voltage ranging from 60 to 140 kVp as well as additional MDCT protocols with dedicated spectral shaping via tin prefiltration. Irrespective of scanner type, all examinations were conducted in ultra-high-resolution (UHR) scan mode. For reconstruction of UHR-CBCT scans an additional iterative metal artifact reduction algorithm was employed, an image correction tool which cannot be used in combination with UHR-MDCT. To compare applied radiation doses between both scanners, the volume computed tomography dose index for a 16 cm phantom (CTDIvol) was evaluated. Images were assessed regarding subjective and objective image quality. Without automatic tube current modulation or tube potential control, radiation doses ranged between 1.3 mGy (with 70 kVp and 50.0 effective mAs) and 75.2 mGy (with 140 kVp and 383.0 effective mAs) in UHR-MDCT. Using the pulsed image acquisition method of the CBCT scanner, CTDIvol ranged between 2.3 mGy (with 60 kVp and 0.6 mean mAs per pulse) and 61.0 mGy (with 133 kVp and 2.5 mean mAs per pulse). In essence, all UHR-CBCT protocols employing a tube potential of 80 kVp or more were found to provide superior overall image quality and artifact reduction compared to UHR-MDCT (all p < .050). Interrater reliability of seven radiologists regarding image quality was substantial for tissue assessment and moderate for artifact assessment with Fleiss kappa of 0.652 (95% confidence interval 0.618-0.686; p < 0.001) and 0.570 (95% confidence interval 0.535-0.606; p < 0.001), respectively. Our results demonstrate that the UHR-CBCT scan mode of a twin robotic X-ray system facilitates excellent visualization of the appendicular skeleton in the presence of metal implants. Achievable image quality and artifact reduction are superior to dose-comparable UHR-MDCT and even MDCT protocols employing spectral shaping with tin prefiltration do not achieve the same level of artifact reduction in adjacent soft tissue.


Assuntos
Artefatos , Procedimentos Cirúrgicos Robóticos , Tomografia Computadorizada de Feixe Cônico/métodos , Humanos , Tomografia Computadorizada Multidetectores/métodos , Doses de Radiação , Reprodutibilidade dos Testes , Estanho , Raios X
15.
Sci Rep ; 12(1): 15276, 2022 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-36088475

RESUMO

Beam hardening artefacts induced by highly-dense material (e.g. metal) is a common quality issue in maxillofacial Cone Beam Computed Tomography (CBCT-) images. This experimental and analytical study investigated attenuation patterns of two typical dental implant materials: zirconia-ceramic and pure titanium. By application of different x-ray beam energies (60, 70, 80, 90 [kVp]) energy-dependent attenuation of these materials is assessed and the resulting artefact induction in the resulting CBCT-images evaluated. A zirconia (Y-TZP-) implant ([Formula: see text]: 4.1 mm) and a pure titanium rod ([Formula: see text]: 4.0 mm) were exposed in a commercial CBCT (3D Accuitomo 170). The raw two-dimensional (2D) projection radiographs the CBCT utilizes for three-dimensional reconstruction applied for acquisition of attenuation profiles through the circular central slice of the implant-phantom images. Distances the x-rays traverse through the implant-phantoms at this location were computed. Using this information and the linear attenuation coefficient, transmission and attenuation was computed for each material and beam energy. These data were related to beam hardening artefacts that were assessed in the axial reconstructions of the implants' CBCT images. Transmission of titanium for all peak kilovoltages (kVp) was higher and approximately 200% that of Y-TZP at 60 kVp versus 530% at 90 kVp. At 4 mm diameter transmission for Y-TZP was only approximately 5 % for all four beam-energies. In agreement with this finding, beam hardening artefacts for Y-TZP could not be reduced using higher energies, whereas for titanium they decreased with increasing energy. For the energy spectrum used in this study (60-90 kVp), beam hardening caused by titanium can be reduced using higher energies while this is not the case for zirconia-ceramic (Y-TZP).


Assuntos
Artefatos , Tomografia Computadorizada de Feixe Cônico Espiral , Titânio , Zircônio
16.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 1145-1148, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-36085641

RESUMO

Continuous Glucose Monitoring (CGM) sensors micro-invasively provide frequent glucose readings, improving the management of Type 1 diabetic patients' life and making available reach data-sets for retrospective analysis. Unlikely, CGM sensors are subject to failures, such as compression artifacts, that might impact on both real-time and respective CGM use. In this work is focused on retrospective detection of compression artifacts. An in-silico dataset is generated using the T1D UVa/Padova simulator and compression artifacts are subsequently added in known position, thus creating a dataset with perfectly accurate faulty/not-faulty labels. The problem of compression artifact detection is then faced with supervised data-driven techniques, in particular using Random Forest algorithm. The detection performance guaranteed by the method on in-silico data is satisfactory, opening the way for further analysis on real-data.


Assuntos
Artefatos , Automonitorização da Glicemia , Glicemia , Glucose , Humanos , Estudos Retrospectivos
17.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 3878-3881, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-36085645

RESUMO

Automatic lesion segmentation in breast ultrasound (BUS) images aids in the diagnosis of breast cancer, the most common type of cancer in women. Accurate lesion segmentation in ultrasound images is a challenging task due to speckle noise, artifacts, shadows, and lesion variability in size and shape. Recently, convolutional neural networks have demonstrated impressive results in medical image segmentation tasks. However, the lack of public benchmarks and a standardized evaluation method hampers the networks' performance comparison. This work presents a benchmark of seven state-of-the-art methods for the automatic breast lesion segmentation task. The methods were evaluated on a multi-center BUS dataset composed of three public datasets. Specifically, the U-Net, Dynamic U-Net, Semantic Segmentation Deep Residual Network with Variational Autoencoder (SegResNetVAE), U-Net Transformers, Residual Feedback Network, Multiscale Dual Attention-Based Network, and Global Guidance Network (GG-Net) architectures were evaluated. The training was performed with a combination of the cross-entropy and Dice loss functions and the overall performance of the networks was assessed using the Dice coefficient, Jaccard index, accuracy, recall, specificity, and precision. Despite all networks having obtained Dice scores superior to 75%, the GG-Net and SegResNetVAE architectures outperform the remaining methods, achieving 82.56% and 81.90%, respectively. Clinical Relevance- The results of this study allowed to prove the potential of deep neural networks to be used in clinical practice for breast lesion segmentation also suggesting the best model choices.


Assuntos
Neoplasias da Mama , Aprendizado Profundo , Artefatos , Neoplasias da Mama/diagnóstico por imagem , Feminino , Humanos , Ultrassonografia , Ultrassonografia Mamária
18.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 3718-3722, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-36085686

RESUMO

Urodynamics is the current gold-standard for diagnosing lower urinary tract dysfunction, but uses non-physiologically fast, retrograde cystometric filling to obtain a brief snapshot of bladder function. Ambulatory urodynamics allows physicians to evaluate bladder function during natural filling over longer periods of time, but artifacts generated from patient movement necessitate the use of an abdominal pressure sensor, which makes long-term monitoring and feedback for closed-loop treatment impractical. In this paper, we analyze the characteristics of single-channel bladder pressure signals from human and feline datasets, and present an algorithm designed to estimate detrusor pressure, which is useful for diagnosis and treatment. We utilize multiresolution analysis techniques to maximize the attenuation of probable abdominal pressure components in the vesical pressure signal. Results indicate a strong correlation, averaging 0.895 ± 0.121 (N = 40) and 0.812 ± 0.113 (N = 16) between the estimated detrusor pressure obtained by the proposed method and recorded urodynamic data from human and feline subjects, respectively. Clinical Relevance- This work establishes that signal pro-cessing techniques may be applied to vesical pressure alone to accurately reconstruct pressures generated independently by the detrusor muscle. This is relevant for emerging sensors that measure vesical pressure alone or for data analysis of bladder pressure in ambulatory subjects which contains significant abdominal pressure artifacts.


Assuntos
Bexiga Urinária , Urodinâmica , Algoritmos , Instituições de Assistência Ambulatorial , Animais , Artefatos , Gatos , Humanos
19.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 599-602, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-36085691

RESUMO

Ker NL is a general kernel-based framework for auto calibrated reconstruction method, which does not need any explicit formulas of the kernel function for characterizing nonlinear relationships between acquired and unacquired k-space data. It is non-iterative without requiring a large amount of computational costs. Since the limited autocalibration signals (ACS) are acquired to perform KerNL calibration and the calibration suffers from the overfitting problem, more training data can improve the kernel model accuracy. In this work, virtual conjugate coil data are incorporated into the KerNL calibration and estimation process for enhancing reconstruction performance. Experimental results show that the proposed method can further suppress noise and aliasing artifacts with fewer ACS data and higher acceleration factors. Computation efficiency is still retained to keep fast reconstruction with the random projection.


Assuntos
Aceleração , Artefatos , Calibragem
20.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 3870-3873, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-36085718

RESUMO

Optical coherence tomography is widely used to provide high resolution images from retina. During data acquisition, several artifacts may be associated with OCT images which clearly remove information of retinal layers and degrade the quality of images. Manual assessment of the acquired OCT images is hard and time consuming. Therefore, an automatic quality control step is necessary to detect poor images for next decisions of eliminating them and even re-scanning. In this study, a novel automatic quality control methodology is proposed for early assessment of the OCT images quality by employing stochastic differential equations (SDE). In this method α-stable nature of OCT images is represented by applying a fractional Laplacian filter and parameters of the obtained α-stable are fed to an SVM to automatically detect high quality vs poor quality images. The simulation results on a large dataset of normal and abnormal OCT images show that proposed method has outstanding performance in detection of poor vs high quality images. The methodology is applicable to the image quality assessment of other OCT scanning devices as well. Clinical Relevance- Automatic quality control assessment of retinal OCT images provides reliable data for diagnosis of retinal and systematic diseases in clinical applications.


Assuntos
Retina , Tomografia de Coerência Óptica , Artefatos , Simulação por Computador , Controle de Qualidade , Retina/diagnóstico por imagem
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...