Computational cost of GNG3D algorithm for mesh simplification

In this paper we present a study of the computational cost of the GNG3D algorithm for mesh optimization. This algorithm has been implemented taking as a basis a new method which is based on neural networks and consists on two differentiated phases: an optimization phase and a reconstruction phase. The optimization phase is developed applying an optimization algorithm based on the Growing Neural Gas model, which constitutes an unsupervised incremental clustering algorithm. The primary goal of this phase is to obtain a simplified set of vertices representing the best approximation of the original 3D object. In the reconstruction phase we use the information provided by the optimization algorithm to reconstruct the faces thus obtaining the optimized mesh. The computational cost of both phases is calculated, showing some examples.

A Comparative Study of Registration Methods for RGB-D Video of Static Scenes

The use of RGB-D sensors for mapping and recognition tasks in robotics or, in general, for virtual reconstruction has increased in recent years. The key aspect of these kinds of sensors is that they provide both depth and color information using the same device. In this paper, we present a comparative analysis of the most important methods used in the literature for the registration of subsequent RGB-D video frames in static scenarios. The analysis begins by explaining the characteristics of the registration problem, dividing it into two representative applications: scene modeling and object reconstruction. Then, a detailed experimentation is carried out to determine the behavior of the different methods depending on the application. For both applications, we used standard datasets and a new one built for object reconstruction.

Characteristics of samples obtained during the expedition to Bolshoy Lyakhovsky Island in July/August 2014

The German-Russian project CARBOPERM - Carbon in Permafrost, origin, quality, quantity, and degradation and microbial turnover - is devoted to studying soil organic matter history, degradation and turnover in coastal lowlands of Northern Siberia. The multidisciplinary project combines research from various German and Russian institutions and runs from 2013 to 2016. The project aims assessing the recent and the ancient trace gas budget over tundra soils in northern Siberia. Studied field sites are placed in the permafrost of the Lena Delta and on Bol'shoy Lyakhovsky, the southernmost island of the New Siberian Archipelago in the eastern Laptev Sea. Field campaigns to Bol'shoy Lyakhovsky in 2014 (chapter 2) were motivated by research on palaeoenvironmental and palaeoclimate reconstruction, sediment dating, near surface geophysics and microbiological research. In particular the field campaigns focussed on: - coring Quaternary strata with a ages back to ~200.000 years ago as found along the southern coast; they allow tracing microbial communities and organic tracers (i.e. lipids and biomarkers, sedimentary DNA) in the deposits across two climatic cycles (chapter 3), - instrumenting a borehole with a thermistor chain for measuring permafrost temperatures (chapter 3), - sampling Quaternary strata for dating permafrost formation periods based on the optical stimulated luminescence (OSL) technique (chapter 4), - sampling soil and geologic formations for carbon content in order to highlight potential release of CO2 and methane based on incubation experiments (chapter 5), - profiling near surface permafrost using ground-penetrating radar and geoelectrics for defining the spatial depositional context, where the cores are located (chapters 6 + 7).

American relief for students ...

Cover-title.

Yazoo : or, On the picket line of freedom in the South. A personal narrative /

Mode of access: Internet.

Heterologous RNA encapsidated in pariacoto virus-like particles forms a dodecahedral cage similar to genomic RNA in wild-type virions

The genome of some icosahedral RNA viruses plays an essential role in capsid assembly and structure. In T=3 particles of the nodavirus Pariacoto virus (PaV), a remarkable 35% of the single-stranded RNA genome is icosahedrally ordered. This ordered RNA can be visualized at high resolution by X-ray crystallography as a dodecahedral cage consisting of 30 24-nucleotide A-form RNA duplex segments that each underlie a twofold icosahedral axis of the virus particle and interact extensively with the basic N-terminal region of 60 subunits of the capsid protein. To examine whether the PaV genome is a specific determinant of the RNA structure, we produced virus-like particles (VLPs) by expressing the wild-type capsid protein open reading frame from a recombinant baculovirus. VLPs produced by this system encapsidated similar total amounts of RNA as authentic virus particles, but only about 6% of this RNA was PaV specific, the rest being of cellular or baculovirus origin. Examination of the VLPs by electron cryomicroscopy and image reconstruction at 15.4-Angstrom resolution showed that the encapsidated RNA formed a dodecahedral cage similar to that of wild-type particles. These results demonstrate that the specific nucleotide sequence of the PaV genome is not required to form the dodecahedral cage of ordered RNA.

Description of manganese deposits collected by R/V Nothwind during the 1963 expedition in the Laptev sea

The 400-km-wide, low gradient Laptev Sea continental shelf consists of flat terrace-like features at regular depth intervals from 10 to 40 m below present sea level. The five large submarine valleys traversing the shelf do not continuously grade seaward, but contain elongated, closed basins. These terraces and closed basins plus deltaic sediments associated with the submarine valleys quite possibly mark sea level Stillstands, and enable reconstruction of the paleogeography of the Laptev Sea shore line at five periods during post-Wisconsin (Holocene) time. Radiocarbon dates on the silty-clay to clayey-silt sediments from cores of the northeastern Laptev Sea indicate average sedimentation intensity of 2 to 15 mg/cm2/yr. The presence of manganese nodules and crusts in surface samples from less than 55 m depths and a general decrease in total foraminiferal abundances with depth in the cores suggest that the present deposition rate is less than when sea level was lower. The main components of the shelf deposits are near- shore sediments which were spread over the shelf as Holocene sea level fluctuated and marine currents distributed modern fine sediment. Rare silty-sand layers and the coarser nuclei of the manganese crusts and nodules indicate ice rafting. However, this mechanism is probably only locally important as a significant transporting agent.

Estudo e aplicação da transformada de Fourier na regularização de dados sísmicos na exploração de petróleo

In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.

Estudo e aplicação da transformada de Fourier na regularização de dados sísmicos na exploração de petróleo

In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Modelos de modernización para el desarrollismo: el influjo de las propuestas estadounidenses en el Servicio de Extensión Agraria (1955-1975)

Con este trabajo nos proponemos estudiar las políticas agrarias del franquismo y particularmente la creación y actuación del Servicio de Extensión Agraria (1955) en el contexto de la difusión de la Teoría de la Modernización. Comenzaremos con una contextualización de las relaciones culturales entre España y los EE.UU. y su potencial proyección sobre el ámbito rural. A continuación, prestaremos atención a la impronta del modelo extensionista norteamericano en la organización y metodología del Servicio de Extensión Agraria. Sin perder de vista la importancia de la escala estatal para la implementación y adaptación de las distintas políticas agrarias, atenderemos al contexto político e ideológico internacional como elemento que permite ampliar la comprensión y estudio de dichas políticas. En ese sentido, propondremos finalmente una primera aproximación comparativa al estudio del SEA en relación con diferentes experiencias de extensionismo agrario en Latinoamérica.

Líneas posibles de avance del modelo de Sraffa

Diversas consideraciones históricas e ideológicas han impedido la difusión de la obra fundamental de Sraffa Producción de mercancías por medio de mercancías. La obra de Sraffa ha sido estudiada fundamentalmente en sus aspectos matemáticos por economistas tales como Garegnani, Abraham-Frois, Pasinetti, Steedman, Kurz, Roncaglia, etc. pero sin desarrollar apenas sus aspectos teóricos y económicos. En este artículo se hacen algunas consideraciones sobre posibles desarrollos del libro de Sraffa a partir de su propio esquema de pensamiento.

On precise three-dimensional environment modeling via UAV-based photogrammetric systems

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.

Dynamika dostępu kobiet do studiów politechnicznych. Studium z socjologii edukacji

Wydział Studiów Edukacyjnych: Zakład Edukacji Wielokulturowej i Badań Nad Nierównościami Społecznymi

Evaluación de las propiedades clinimétricas de la escala POSAS y su aplicación en pacientes de la Fundación del Quemado en Bogotá

•Objetivos: Se tradujo, adaptó y evaluaron las propiedades clinimétricas de la escala POSAS en pacientes con cicatrices hipertróficas (CHT) y queloides (CQ) cómo secuelas de quemadura, que fueron manejados con Z plastias en la Fundación del Quemado en Bogotá (Colombia), entre Junio de 2015 a Abril de 2016. •Métodos: Estudio de evaluación de las propiedades clinimétricas de una escala. Se hizo una traducción y adaptación transcultural siguiendo el método de traducción-retrotraducción. Se aplicó el instrumento adaptado a cincuenta y dos pacientes (n=52) antes y después de la intervención quirúrgica. Se evaluó la validez, confiabilidad, sensibilidad al cambio y la utilidad de la escala. •Resultados: Se hallaron diferencias significativas en los puntajes obtenidos del Observador y del Paciente, antes y después de la intervención quirúrgica (p<0.000); a excepción de prurito. La escala POSAS demostró ser altamente confiable para la Escala del Observador y del Paciente (α = 0.912 y 0.765). Hubo alta correlación en las evaluaciones de dos observadores para las variables ordinales de la Escala del Observador (r>0.6). La concordancia entre las evaluaciones de dos observadores para las variables categóricas de la Escala del Paciente fue buena para la evaluación antes de la intervención para pigmentación y relieve (κ>0.61). Se demostró que el instrumento es capaz de detectar cambios clínicos en el tiempo (p<0.0000), a excepción de prurito (p= 0.271). •Conclusiones: La escala POSAS demostró ser un instrumento válido, confiable y útil para evaluar la calidad de la cicatriz en pacientes con CHT y CQ cómo secuelas de quemadura.