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1.
Sensors (Basel) ; 22(21)2022 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-36366069

RESUMO

As most of the outcropping and shallow mineral deposits have been found, new technology is imperative to finding the hidden critical mineral deposits required to transition to renewable energy. One such new technique, called ambient seismic noise tomography, has shown promise in recent years as a low-cost, low environmental impact method that can image under cover and at depth. Wireless and compact nodal seismic technology has been instrumental to enable industry applications of ambient noise tomography, but these devices are designed for the active seismic reflection method and do not have the required sensitivity at low frequencies for ambient noise tomography, and real-time data transmission in remote locations requires significant infrastructure to be installed. In this paper, we show the development and testing of the Geode-a real-time seismic node purpose-built by Fleet Space Technologies for ambient seismic noise tomography on exploration scales. We discuss the key differences between current nodal technology and the Geode and show results of a field trial where the performance of the Geode is compared with a commercially popular nodal geophone. The use of a 2 Hz high sensitivity geophone and low noise digitiser results in an instrument noise floor that is more than 30 dB lower below 5 Hz than nodes that are commonly used in the industry. The increased sensitivity results in signal-to-noise ratios in the cross-correlation functions in the field trial that are more than double that of commercially available nodal geophone at low frequencies. When considering the full bandwidth of retrievable correlations in our study, using the Geode would reduce the required recording time from 75 h to 32 h to achieve an average signal-to-noise ratio in the cross-correlation functions of 10. We also discuss the integration of a real-time direct-to-satellite Internet of Things (DtS-IoT) modem in the Geode, which, together with edge processing of seismic data directly on the Geode, enables us to image the subsurface in real-time. During the field trial, the Geodes successfully transmitted more than 90% of the available preprocessed data packets. The Geode is compact enough so that several devices can be carried and installed by one field technician, whilst the array of stations do not require a base station to transmit data to the cloud for further processing. We believe this is the future of passive seismic surveys and will result in faster and more dynamic seismic imaging capabilities analogous to the medical imaging community, increasing the pace at which new mineral deposits are discovered.


Assuntos
Internet das Coisas , Ruído , Meio Ambiente , Tomografia
2.
J Biophotonics ; 15(11): e202200126, 2022 11.
Artigo em Inglês | MEDLINE | ID: mdl-36328059

RESUMO

Cerenkov luminescence tomography (CLT) is a promising three-dimensional imaging technology that has been actively investigated in preclinical studies. However, because of the ill-posedness in the inverse problem of CLT reconstruction, the reconstruction performance is still not satisfactory for broad biomedical applications. In this study, a novel weighted auxiliary set matching pursuit (WASMP) method was explored to enhance the accuracy of CLT reconstruction. The numerical simulations and in vivo imaging studies using tumor-bearing mice models were conducted to evaluate the performance of the WASMP method. The results of the above experiments proved that the WASMP method achieved superior reconstruction performance than other approaches in terms of positional accuracy and shape recovery. It further demonstrates that the atom selection strategy proposed in this study has a positive effect on improving the accuracy of atoms. The proposed WASMP improves the accuracy for CLT reconstruction for biomedical applications.


Assuntos
Glioma , Tomografia Óptica , Animais , Camundongos , Tomografia Óptica/métodos , Luminescência , Tomografia , Tomografia Computadorizada por Raios X , Imageamento Tridimensional/métodos , Glioma/diagnóstico por imagem , Algoritmos , Imagens de Fantasmas
3.
Phys Med Biol ; 67(22)2022 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-36317273

RESUMO

Objective. Open magnetic induction tomography (MIT) is a promising technique for detecting the intracranial hemorrhage due to the non-radioactive, non-invasive and portable features. However, severe inhomogeneity of the sensitivity distribution under the open MIT sensor array and the ill-conditioned nature of MIT inverse problem limit the imaging quality in hemorrhage reconstruction. More accurate and robust imaging algorithms are urgently needed in clinical diagnosis.Approach.In this study, the space-constrained optimized Tikhonov regularization (SOTR) method is proposed for 3D hemorrhage reconstruction by open MIT. The sensitivity matrix is optimized according to the characteristics of sensitivity distribution under the open MIT sensor array. To test the performance of the SOTR method, 3D anatomical head models with hemorrhages in different volumes and locations were established. The images of the hemorrhages were reconstructed by the Tikhonov regularization (TR), total variation (TV) regularization, isotropic SOTR, and anisotropic SOTR method. Correlation coefficientCC,localization errorLE,and volume errorVEwere calculated to evaluate the hemorrhage imaging quality. Mainresults. Compared with the traditional sensitivity matrix, the optimized sensitivity matrix has smaller column number and better uniformity, which alleviates the under-determined and ill-conditioned problem of MIT. The imaging results indicate that both the isotropic and anisotropic SOTR methods can effectively improve the reconstruction accuracy for the location and volume of the hemorrhages. Moreover, compared with the TR and TV methods, the two SOTR methods are more robust against the measurement noise.Significance. The proposed method improves the imaging quality of the intracranial hemorrhage, which promotes the clinical applications of open MIT.


Assuntos
Processamento de Imagem Assistida por Computador , Tomografia , Humanos , Processamento de Imagem Assistida por Computador/métodos , Tomografia/métodos , Algoritmos , Hemorragias Intracranianas , Fenômenos Magnéticos , Imagens de Fantasmas
5.
Korean J Intern Med ; 37(6): 1176-1185, 2022 11.
Artigo em Inglês | MEDLINE | ID: mdl-36375488

RESUMO

BACKGROUND/AIMS: Acute upper gastrointestinal (UGI) bleeding is a significant emergency situation with a mortality rate of 2% to 10%. Therefore, initial risk stratification is important for proper management. We aimed to evaluate the role of contrast-enhanced multidetector computed tomography (MDCT) for risk stratification in patients with acute UGI bleeding in the emergency room (ER). METHODS: This retrospective study included patients with UGI bleeding in the ER. Glasgow-Blatchford risk score-computed tomography (GBS-CT) was assessed using a combination of GBS and the MDCT scan scoring system. RESULTS: Of the 297 patients with UGI bleeding, 124 (41.8%) underwent abdominal MDCT. Among them, 90.3% were classified as high-risk by GBS, and five patients died (4.0%). Rebleeding occurred in nine patients (7.3%). The high-risk GBS-CT group had significantly higher in-hospital mortality (10.5% in high-risk vs. 1.4% in moderate risk vs. 0% in low-risk, p = 0.049), transfusion amount (p < 0.001), and endoscopic hemostasis (p < 0.001) compared to the moderate- and low-risk groups. CONCLUSION: Adding MDCT scans to the existing validated prognosis model when predicting the risk of UGI bleeding in patients in the ER plays a significant role in determining in-hospital mortality, transfusions, and the need for endoscopic hemostasis.


Assuntos
Serviço Hospitalar de Emergência , Hemorragia Gastrointestinal , Humanos , Estudos Retrospectivos , Medição de Risco/métodos , Índice de Gravidade de Doença , Hemorragia Gastrointestinal/diagnóstico por imagem , Hemorragia Gastrointestinal/etiologia , Hemorragia Gastrointestinal/terapia , Doença Aguda , Fatores de Risco , Prognóstico , Tomografia Computadorizada por Raios X , Tomografia , Curva ROC
7.
Sci Rep ; 12(1): 17786, 2022 Oct 22.
Artigo em Inglês | MEDLINE | ID: mdl-36273026

RESUMO

Three-dimensional reconstruction of the analysed volume is one of the main goals of atom probe tomography (APT) and can deliver nearly atomic resolution (~ 0.2 nm spatial resolution) and chemical information with a mass sensitivity down to the ppm range. Extending this technique to frozen biological systems would have an enormous impact on the structural analysis of biomolecules. In previous works, we have shown that it is possible to measure frozen liquids with APT. In this paper, we demonstrate the ability of APT to trace nanoscale precipitation in frozen natural honey. While the mass signals of the common sugar fragments CxHy and CxOyHz overlap with (H2O)nH from water, we achieved correct stoichiometric values via different interpretation approaches for the peaks and thus determined the water content reliably. Next, we use honey to investigate the spatial resolution capabilities as a step toward the measurement of biological molecules in solution in 3D with sub-nanometer resolution. This may take analytical techniques to a new level, since methods of chemical characterization for cryogenic samples, especially biological samples, are still limited.


Assuntos
Mel , Tomografia/métodos , Água/química , Açúcares
8.
Sensors (Basel) ; 22(20)2022 Oct 14.
Artigo em Inglês | MEDLINE | ID: mdl-36298152

RESUMO

The advancement of new promising techniques in the field of biomedical imaging has always been paramount for the research community. Recently, ultrasound tomography has proved to be a good candidate for non-invasive and safe diagnostics. In particular, breast cancer imaging may benefit from this approach, as frequent screening and early diagnosis require decreased system size and costs compared to conventional imaging techniques. Furthermore, a major advantage of these approaches consists in the operator-independent feature, which is very desirable compared to conventional hand-held ultrasound imaging. In this framework, the authors present some imaging results on an experimental campaign acquired via an in-house ultrasound tomographic system designed and built at the University of Naples Parthenope. Imaging performance was evaluated via different tests, showing good potentiality in structural information retrieval. This study represents a first proof of concept in order to validate the system and to consider further realistic cases in near future applications.


Assuntos
Tomografia Computadorizada por Raios X , Tomografia , Ultrassonografia
9.
Sensors (Basel) ; 22(20)2022 Oct 18.
Artigo em Inglês | MEDLINE | ID: mdl-36298274

RESUMO

In recent years, it has become increasingly popular to solve inverse problems of various tomography methods with deep learning techniques. Here, a deep residual neural network (ResNet) is introduced to reconstruct the conductivity distribution of a biomedical, voluminous body in magnetic induction tomography (MIT). MIT is a relatively new, contactless and noninvasive tomography method. However, the ill-conditioned inverse problem of MIT is challenging to solve, especially for voluminous bodies with conductivities in the range of biological tissue. The proposed ResNet can reconstruct up to two cuboid perturbation objects with conductivities of 0.0 and 1.0 S/m in the whole voluminous body, even in the difficult-to-detect centre. The dataset used for training and testing contained simulated signals of cuboid perturbation objects with randomised lengths and positions. Furthermore, special care went into avoiding the inverse crime while creating the dataset. The calculated metrics showed good results over the test dataset, with an average correlation coefficient of 0.87 and mean squared error of 0.001. Robustness was tested on three special test cases containing unknown shapes, conductivities and a real measurement that showed error results well within the margin of the metrics of the test dataset. This indicates that a good approximation of the inverse function in MIT for up to two perturbation objects was achieved and the inverse crime was avoided.


Assuntos
Processamento de Imagem Assistida por Computador , Tomografia , Processamento de Imagem Assistida por Computador/métodos , Tomografia/métodos , Magnetismo , Condutividade Elétrica , Redes Neurais de Computação
10.
Phys Med Biol ; 67(21)2022 10 27.
Artigo em Inglês | MEDLINE | ID: mdl-36220011

RESUMO

Objective.Bioluminescence tomography (BLT) is a promising non-invasive optical medical imaging technique, which can visualize and quantitatively analyze the distribution of tumor cells in living tissues. However, due to the influence of photon scattering effect and ill-conditioned inverse problem, the reconstruction result is unsatisfactory. The purpose of this study is to improve the reconstruction performance of BLT.Approach.An alternating Bregman proximity operators (ABPO) method based on TVSCAD regularization is proposed for BLT reconstruction. TVSCAD combines the anisotropic total variation (TV) regularization constraints and the non-convex smoothly clipped absolute deviation (SCAD) penalty constraints, to make a trade-off between the sparsity and edge preservation of the source. ABPO approach is used to solve the TVSCAD model (ABPO-TVSCAD for short). In addition, to accelerate the convergence speed of the ABPO, we adapt the strategy of shrinking the permission source region, which further improves the performance of ABPO-TVSCAD.Main results.The results of numerical simulations andin vivoxenograft mouse experiment show that our proposed method achieved superior accuracy in spatial localization and morphological reconstruction of bioluminescent source.Significance.ABPO-TVSCAD is an effective and robust reconstruction method for BLT, and we hope that this method can promote the development of optical molecular tomography.


Assuntos
Algoritmos , Tomografia Óptica , Animais , Camundongos , Medições Luminescentes , Tomografia/métodos , Tomografia Óptica/métodos , Tomografia Computadorizada por Raios X , Imagens de Fantasmas
11.
Adv Exp Med Biol ; 1380: 1-16, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36306092

RESUMO

The electromagnetic properties of body tissues depend on numerous factors, the most important of which are ionic concentrations and, particularly in the low-frequency regime, membrane density and geometry. In this chapter, the characteristics of these properties and their spectra are introduced. The properties measured by different types of MR-based methods are described.


Assuntos
Processamento de Imagem Assistida por Computador , Imageamento por Ressonância Magnética , Processamento de Imagem Assistida por Computador/métodos , Imagens de Fantasmas , Imageamento por Ressonância Magnética/métodos , Algoritmos , Impedância Elétrica , Fenômenos Eletromagnéticos , Tomografia/métodos
12.
Adv Exp Med Biol ; 1380: 111-134, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36306096

RESUMO

Magnetic resonance electrical impedance tomography (MREIT) can provide internal conductivity distributions at low frequency (below 1 kHz) induced by an external injecting current. In MREIT, we inject current I using at least one pair of electrodes into an object to produce internal current density J = (Jx, Jy, Jz) and magnetic flux density B = (Bx, By, Bz) in the object. An MRI scanner with its main magnetic field pointing the z direction is used to measure the induced magnetic flux density (Bz) caused by external current injection. To avoid the interaction of external current injection with MRI acquisitions, it is important to synchronize the current injection with MRI sequence. In the first part of this chapter, we will discuss the practical aspects of a successful MREIT experiment. Following a brief introduction to the experiment setup, we will then summarize various MRI sequences used for MREIT, magnetic flux density measurement, and image reconstructions for MREIT experiments.


Assuntos
Algoritmos , Imageamento por Ressonância Magnética , Imagens de Fantasmas , Impedância Elétrica , Imageamento por Ressonância Magnética/métodos , Espectroscopia de Ressonância Magnética , Processamento de Imagem Assistida por Computador/métodos , Condutividade Elétrica , Tomografia/métodos
13.
Adv Exp Med Biol ; 1380: 157-183, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36306098

RESUMO

Magnetic Resonance Electrical Impedance Tomography (MREIT) is a high-resolution bioimpedance imaging technique that has developed over a period beginning in the early 1990s to measure low-frequency (<1 kHz) tissue electrical properties. Low-frequency electrical properties are particularly important because they provide valuable information on cell structures and ionic composition of tissues, which may be very useful for diagnostic purposes. MREIT uses one component of the magnetic flux density data induced due to an exogenous-current administration, measured using an MRI machine, to reconstruct isotropic or anisotropic electrical property distributions. The MREIT technique typically requires two linearly independent current administrations to reconstruct conductivity uniquely. Since its invention, researchers have explored its potential for measuring electrical conductivity in regions such as the brain and muscle tissue. It has also been investigated in disease models, for example, cerebral ischemia and early tumor detection. In this chapter, we aim to provide a solid foundation of the different MREIT image reconstruction algorithms, including both isotropic and anisotropic conductivity reconstruction approaches. We will also explore the newly developed diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) method, a practical method for anisotropic tissue property imaging, at the end of the chapter.


Assuntos
Algoritmos , Imageamento por Ressonância Magnética , Impedância Elétrica , Imageamento por Ressonância Magnética/métodos , Espectroscopia de Ressonância Magnética , Anisotropia , Condutividade Elétrica , Tomografia/métodos , Imagens de Fantasmas
14.
Adv Exp Med Biol ; 1380: 185-202, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36306099

RESUMO

This chapter explains the magnetic resonance electrical impedance tomography (MREPT) technique used to image electrical properties at high frequencies. The chapter describes the MREPT data acquisition methods, current state-of-the-art image reconstruction algorithms, and experiments with phantoms, animals, and humans.


Assuntos
Imageamento por Ressonância Magnética , Tomografia , Animais , Humanos , Impedância Elétrica , Tomografia/métodos , Imageamento por Ressonância Magnética/métodos , Imagens de Fantasmas , Espectroscopia de Ressonância Magnética , Processamento de Imagem Assistida por Computador/métodos , Algoritmos
15.
Adv Exp Med Biol ; 1380: 83-110, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36306095

RESUMO

Phantom objects are commonly employed in MRI systems as stable substitutes for biological tissues to ensure systems for measuring images are operating correctly and safely. For magnetic resonance electrical impedance tomography (MREIT) and magnetic resonance electrical property tomography (MREPT), conductivity or permittivity phantoms play an important role in checking MRI pulse sequences, MREIT equipment performance, and algorithm validation. The construction of these phantoms is explained in this chapter. In the first part, materials used for phantom construction are introduced. Ingredients for modifying the electromagnetic properties and relaxation times are presented, and the advantages and disadvantages of aqueous, gel, and hybrid conductivity phantoms are explained. The devices and methods used to confirm phantom electromagnetic properties are explained. Next, different types of MREIT electrode materials and the constant current sources used for MREIT studies are discussed. In the last section, we present the results of previous MREIT and MREPT studies.


Assuntos
Processamento de Imagem Assistida por Computador , Imageamento por Ressonância Magnética , Processamento de Imagem Assistida por Computador/métodos , Impedância Elétrica , Imagens de Fantasmas , Imageamento por Ressonância Magnética/métodos , Tomografia/métodos , Algoritmos , Condutividade Elétrica
16.
Front Public Health ; 10: 1012929, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36187623

RESUMO

Purpose: This study aimed to develop a deep learning model to generate a postoperative corneal axial curvature map of femtosecond laser arcuate keratotomy (FLAK) based on corneal tomography using a pix2pix conditional generative adversarial network (pix2pix cGAN) for surgical planning. Methods: A total of 451 eyes of 318 nonconsecutive patients were subjected to FLAK for corneal astigmatism correction during cataract surgery. Paired or single anterior penetrating FLAKs were performed at an 8.0-mm optical zone with a depth of 90% using a femtosecond laser (LenSx laser, Alcon Laboratories, Inc.). Corneal tomography images were acquired from Oculus Pentacam HR (Optikgeräte GmbH, Wetzlar, Germany) before and 3 months after the surgery. The raw data required for analysis consisted of the anterior corneal curvature for a range of ± 3.5 mm around the corneal apex in 0.1-mm steps, which the pseudo-color corneal curvature map synthesized was based on. The deep learning model used was a pix2pix conditional generative adversarial network. The prediction accuracy of synthetic postoperative corneal astigmatism in zones of different diameters centered on the corneal apex was assessed using vector analysis. The synthetic postoperative corneal axial curvature maps were compared with the real postoperative corneal axial curvature maps using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR). Results: A total of 386 pairs of preoperative and postoperative corneal tomography data were included in the training set, whereas 65 preoperative data were retrospectively included in the test set. The correlation coefficient between synthetic and real postoperative astigmatism (difference vector) in the 3-mm zone was 0.89, and that between surgically induced astigmatism (SIA) was 0.93. The mean absolute errors of SIA for real and synthetic postoperative corneal axial curvature maps in the 1-, 3-, and 5-mm zone were 0.20 ± 0.25, 0.12 ± 0.17, and 0.09 ± 0.13 diopters, respectively. The average SSIM and PSNR of the 3-mm zone were 0.86 ± 0.04 and 18.24 ± 5.78, respectively. Conclusion: Our results showed that the application of pix2pix cGAN can synthesize plausible postoperative corneal tomography for FLAK, showing the possibility of using GAN to predict corneal tomography, with the potential of applying artificial intelligence to construct surgical planning models.


Assuntos
Astigmatismo , Inteligência Artificial , Astigmatismo/cirurgia , Topografia da Córnea , Humanos , Lasers , Estudos Retrospectivos , Tomografia , Acuidade Visual
17.
Sensors (Basel) ; 22(19)2022 Sep 22.
Artigo em Inglês | MEDLINE | ID: mdl-36236283

RESUMO

Electrical impedance tomography (EIT) has been applied in the field of human-computer interaction due to its advantages including the fact that it is non-invasive and has both low power consumption and a low cost. Previous work has focused on static gesture recognition based on EIT. Compared with static gestures, dynamic gestures are more informative and can achieve more functions in human-machine collaboration. In order to verify the feasibility of dynamic gesture recognition based on EIT, a traditional excitation drive pattern is optimized in this paper. The drive pattern of the fixed excitation electrode is tested for the first time to simplify the measurement process of the dynamic gesture. To improve the recognition accuracy of the dynamic gestures, a dual-channel feature extraction network combining a convolutional neural network (CNN) and gated recurrent unit (GRU), namely CG-SVM, is proposed. The new center distance loss is designed in order to simultaneously supervise the intra-class distance and inter-class distance. As a result, the discriminability of the confusing data is improved. With the new excitation drive pattern and classification network, the recognition accuracy of different interference data has increased by 2.7~14.2%. The new method has stronger robustness, and realizes the dynamic gesture recognition based on EIT for the first time.


Assuntos
Gestos , Reconhecimento Automatizado de Padrão , Algoritmos , Impedância Elétrica , Mãos/diagnóstico por imagem , Humanos , Redes Neurais de Computação , Reconhecimento Automatizado de Padrão/métodos , Tomografia
18.
Appl Opt ; 61(22): G48-G56, 2022 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-36255863

RESUMO

Pharmacokinetic parameter estimation with the support of dynamic diffuse fluorescence tomography (DFT) can provide helpful diagnostic information for tumor differentiation and monitoring. Adaptive extended Kalman filtering (AEKF) as a nonlinear filter method has the merits of high quantitativeness, noise robustness, and initialization independence. In this paper, indirect and direct AEKF schemes combining with a commonly used two-compartment model were studied to estimate the pharmacokinetic parameters based on our self-designed dynamic DFT system. To comprehensively compare the performances of both schemes, the selection of optimal noise covariance matrices affecting estimation results was first studied, then a series of numerical simulations with the metabolic time ranged from 4.16 min to 38 min was carried out and quantitatively evaluated. The comparison results show that the direct AEKF outperforms the indirect EKF in estimation accuracy at different metabolic velocity and demonstrates stronger stability at the large metabolic velocity. Furtherly, the in vivo experiment was conducted to achieve the indocyanine green pharmacokinetic-rate images in the mouse liver. The experimental results confirmed the capability of both schemes to estimate the pharmacokinetic-rate images and were in agreement with the theory predictions and the numerical simulation results.


Assuntos
Verde de Indocianina , Tomografia , Camundongos , Animais , Fluorescência , Tomografia/métodos , Simulação por Computador , Tomografia Computadorizada por Raios X
19.
Opt Express ; 30(20): 35282-35299, 2022 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-36258483

RESUMO

Cerenkov luminescence tomography (CLT) provides a powerful optical molecular imaging technique for non-invasive detection and visualization of radiopharmaceuticals in living objects. However, the severe photon scattering effect causes ill-posedness of the inverse problem, and the location accuracy and shape recovery of CLT reconstruction results are unsatisfactory for clinical application. Here, to improve the reconstruction spatial location accuracy and shape recovery ability, a non-negative iterative three operator splitting (NNITOS) strategy based on elastic net (EN) regularization was proposed. NNITOS formalizes the CLT reconstruction as a non-convex optimization problem and splits it into three operators, the least square, L1/2-norm regularization, and adaptive grouping manifold learning, then iteratively solved them. After stepwise iterations, the result of NNITOS converged progressively. Meanwhile, to speed up the convergence and ensure the sparsity of the solution, shrinking the region of interest was utilized in this strategy. To verify the effectiveness of the method, numerical simulations and in vivo experiments were performed. The result of these experiments demonstrated that, compared to several methods, NNITOS can achieve superior performance in terms of location accuracy, shape recovery capability, and robustness. We hope this work can accelerate the clinical application of CLT in the future.


Assuntos
Processamento de Imagem Assistida por Computador , Luminescência , Processamento de Imagem Assistida por Computador/métodos , Compostos Radiofarmacêuticos , Tomografia , Tomografia Computadorizada por Raios X , Algoritmos , Imagens de Fantasmas
20.
PLoS One ; 17(10): e0275891, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36227883

RESUMO

In recent years, insect husbandry has seen an increased interest in order to supply in the production of raw materials, food, or as biological/environmental control. Unfortunately, large insect rearings are susceptible to pathogens, pests and parasitoids which can spread rapidly due to the confined nature of a rearing system. Thus, it is of interest to monitor the spread of such manifestations and the overall population size quickly and efficiently. Medical imaging techniques could be used for this purpose, as large volumes can be scanned non-invasively. Due to its 3D acquisition nature, computed tomography seems to be the most suitable for this task. This study presents an automated, computed tomography-based, counting method for bee rearings that performs comparable to identifying all Osmia cornuta cocoons manually. The proposed methodology achieves this in an average of 10 seconds per sample, compared to 90 minutes per sample for the manual count over a total of 12 samples collected around lake Zurich in 2020. Such an automated bee population evaluation tool is efficient and valuable in combating environmental influences on bee, and potentially other insect, rearings.


Assuntos
Insetos , Tomografia , Animais , Abelhas , Densidade Demográfica
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