An automatic correction tool for relational database schemas

A Web-based tool developed to automatically correct relational database schemas is presented. This tool has been integrated into a more general e-learning platform and is used to reinforce teaching and learning on database courses. This platform assigns to each student a set of database problems selected from a common repository. The student has to design a relational database schema and enter it into the system through a user friendly interface specifically designed for it. The correction tool corrects the design and shows detected errors. The student has the chance to correct them and send a new solution. These steps can be repeated as many times as required until a correct solution is obtained. Currently, this system is being used in different introductory database courses at the University of Girona with very promising results

An automatic correction tool for relational database schemas

A Web-based tool developed to automatically correct relational database schemas is presented. This tool has been integrated into a more general e-learning platform and is used to reinforce teaching and learning on database courses. This platform assigns to each student a set of database problems selected from a common repository. The student has to design a relational database schema and enter it into the system through a user friendly interface specifically designed for it. The correction tool corrects the design and shows detected errors. The student has the chance to correct them and send a new solution. These steps can be repeated as many times as required until a correct solution is obtained. Currently, this system is being used in different introductory database courses at the University of Girona with very promising results

An automatic correction method for the heel effect in digitized mammography images

The most significant radiation field nonuniformity is the well-known Heel effect. This nonuniform beam effect has a negative influence on the results of computer-aided diagnosis of mammograms, which is frequently used for early cancer detection. This paper presents a method to correct all pixels in the mammography image according to the excess or lack on radiation to which these have been submitted as a result of the this effect. The current simulation method calculates the intensities at all points of the image plane. In the simulated image, the percentage of radiation received by all the points takes the center of the field as reference. In the digitized mammography, the percentages of the optical density of all the pixels of the analyzed image are also calculated. The Heel effect causes a Gaussian distribution around the anode-cathode axis and a logarithmic distribution parallel to this axis. Those characteristic distributions are used to determine the center of the radiation field as well as the cathode-anode axis, allowing for the automatic determination of the correlation between these two sets of data. The measurements obtained with our proposed method differs on average by 2.49 mm in the direction perpendicular to the anode-cathode axis and 2.02 mm parallel to the anode-cathode axis of commercial equipment. The method eliminates around 94% of the Heel effect in the radiological image and the objects will reflect their x-ray absorption. To evaluate this method, experimental data was taken from known objects, but could also be done with clinical and digital images.

MR image-based measurement of rates of change in volumes of brain structures. Part 1: Method and validation

A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniforniity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part 11 where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease. (C) 2002 Elsevier Science Inc. All rights reserved.

Correcção automática de respostas de texto livre para a aplicação UNI_NET-Classroom

Ao longo dos tempos foi possível constatar que uma grande parte do tempo dos professores é gasta na componente de avaliação. Por esse facto, há já algumas décadas que a correcção automática de texto livre é alvo de investigação. Sendo a correcção de exercícios efectuada pelo computador permite que o professor dedique o seu tempo em tarefas que melhorem a aprendizagem dos alunos. Para além disso, cada vez mais as novas tecnologias permitem o uso de ferramentas com bastante utilidade no ensino, pois para além de facilitarem a exposição do conhecimento também permitem uma maior retenção da informação. Logo, associar ferramentas de gestão de sala de aula à correcção automática de respostas de texto livre é um desafio bastante interessante. O objectivo desta dissertação foi a realização de um estudo relativamente à área de avaliação assistida por computador em que este trabalho se insere. Inicialmente, foram analisados alguns correctores ortográficos para seleccionar aquele que seria integrado no módulo proposto. De seguida, foram estudadas as técnicas mais relevantes e as ferramentas que mais se enquadram no âmbito deste trabalho. Neste contexto, a ideia foi partir da existência de uma ferramenta de gestão de sala de aula e desenvolver um módulo para a correcção de exercícios. A aplicação UNI_NET-Classroom, que foi a ferramenta para a qual o módulo foi desenvolvido, já continha um componente de gestão de exercícios que apenas efectuava a correcção para as respostas de escolha múltipla. Com este trabalho pretendeu-se acrescentar mais uma funcionalidade a esse componente, cujo intuito é dar apoio ao professor através da correcção de exercícios e sugestão da cotação a atribuir. Por último, foram realizadas várias experiências sobre o módulo desenvolvido, de forma a ser possível retirar algumas conclusões para o presente trabalho. A conclusão mais importante foi que as ferramentas de correcção automática são uma mais-valia para os professores e escolas.

Entorn d'autoaprenentatge per a assignatures d'Enginyeria del Programari

L'aplicació desenvolupada és un entorn web que permetrà als estudiants de la UOC millorarel seu rendiment en les assignatures d'Enginyeria del programari, mitjançant la utilització de l'eina de correcció automàtica de diagrames UML desenvolupada pel grup de recerca GRES-UOC.

Utilización de software de corrección automática en el campo de las ciencias de la salud

We live in an era of profound changes in university education. The implementation of Bologna plan has led us to raise new teaching methodologies, to review the role of the student, competency assessment, the incorporation of ICT. Unthinkable acts, one or two decade ago. The TIC concept is very broad and is attributed to the media, processes and content usage. Inside the supports and platforms, we stress tools that allow automatic correction of exercises, because they are instruments of great educational value because instantly they assess students and provide instant feedback about the knowledge that they have either as message support or note. If the power of these tools, we add the Internet, using e-learning environment, the results allow us to work, edit, evaluate, resolve doubts, and so on, anywhere, anytime. We present part of a platform and the results of its use in the field of health sciences

Automatic prebent customized prosthesis for pectus excavatum minimally invasive surgery correction

Pectus excavatum is the most common deformity of the thorax. A minimally invasive surgical correction is commonly carried out to remodel the anterior chest wall by using an intrathoracic convex prosthesis in the substernal position. The process of prosthesis modeling and bending still remains an area of improvement. The authors developed a new system, i3DExcavatum, which can automatically model and bend the bar preoperatively based on a thoracic CT scan. This article presents a comparison between automatic and manual bending. The i3DExcavatum was used to personalize prostheses for 41 patients who underwent pectus excavatum surgical correction between 2007 and 2012. Regarding the anatomical variations, the soft-tissue thicknesses external to the ribs show that both symmetric and asymmetric patients always have asymmetric variations, by comparing the patients’ sides. It highlighted that the prosthesis bar should be modeled according to each patient’s rib positions and dimensions. The average differences between the skin and costal line curvature lengths were 84 ± 4 mm and 96 ± 11 mm, for male and female patients, respectively. On the other hand, the i3DExcavatum ensured a smooth curvature of the surgical prosthesis and was capable of predicting and simulating a virtual shape and size of the bar for asymmetric and symmetric patients. In conclusion, the i3DExcavatum allows preoperative personalization according to the thoracic morphology of each patient. It reduces surgery time and minimizes the margin error introduced by the manually bent bar, which only uses a template that copies the chest wall curvature.

Automatic modeling of an orthotic bracing for nonoperative correction of PectusCarinatum

Pectus Carinatum is a deformity of the chest wall, characterized by an anterior protrusion of the sternum, often corrected surgically due to cosmetic motivation. This work presents an alternative approach to the current open surgery option, proposing a novel technique based on a personalized orthosis. Two different processes for the orthosis’ personalization are presented. One based on a 3D laser scan of the patient chest, followed by the reconstruction of the thoracic wall mesh using a radial basis function, and a second one, based on a computer tomography scan followed by a neighbouring cells algorithm. The axial position where the orthosis is to be located is automatically calculated using a Ray-Triangle intersection method, whose outcome is input to a pseudo Kochenek interpolating spline method to define the orthosis curvature. Results show that no significant differences exist between the patient chest physiognomy and the curvature angle and size of the orthosis, allowing a better cosmetic outcome and less initial discomfort

Automatic prebent customized prosthesis for pectus excavatum minimally invasive surgery correction

Pectus excavatum is the most common deformity of the thorax. A minimally invasive surgical correction is commonly carried out to remodel the anterior chest wall by using an intrathoracic convex prosthesis in the substernal position. The process of prosthesis modeling and bending still remains an area of improvement. The authors developed a new system, i3DExcavatum, which can automatically model and bend the bar preoperatively based on a thoracic CT scan. This article presents a comparison between automatic and manual bending. The i3DExcavatum was used to personalize prostheses for 41 patients who underwent pectus excavatum surgical correction between 2007 and 2012. Regarding the anatomical variations, the soft-tissue thicknesses external to the ribs show that both symmetric and asymmetric patients always have asymmetric variations, by comparing the patients’ sides. It highlighted that the prosthesis bar should be modeled according to each patient’s rib positions and dimensions. The average differences between the skin and costal line curvature lengths were 84 ± 4 mm and 96 ± 11 mm, for male and female patients, respectively. On the other hand, the i3DExcavatum ensured a smooth curvature of the surgical prosthesis and was capable of predicting and simulating a virtual shape and size of the bar for asymmetric and symmetric patients. In conclusion, the i3DExcavatum allows preoperative personalization according to the thoracic morphology of each patient. It reduces surgery time and minimizes the margin error introduced by the manually bent bar, which only uses a template that copies the chest wall curvature.

Automatic prebent customized prosthesis for pectus excavatum minimally invasive surgery correction

Pectus excavatum is the most common deformity of the thorax. A minimally invasive surgical correction is commonly carried out to remodel the anterior chest wall by using an intrathoracic convex prosthesis in the substernal position. The process of prosthesis modeling and bending still remains an area of improvement. The authors developed a new system, i3DExcavatum, which can automatically model and bend the bar preoperatively based on a thoracic CT scan. This article presents a comparison between automatic and manual bending. The i3DExcavatum was used to personalize prostheses for 41 patients who underwent pectus excavatum surgical correction between 2007 and 2012. Regarding the anatomical variations, the soft-tissue thicknesses external to the ribs show that both symmetric and asymmetric patients always have asymmetric variations, by comparing the patients’ sides. It highlighted that the prosthesis bar should be modeled according to each patient’s rib positions and dimensions. The average differences between the skin and costal line curvature lengths were 84 ± 4 mm and 96 ± 11 mm, for male and female patients, respectively. On the other hand, the i3DExcavatum ensured a smooth curvature of the surgical prosthesis and was capable of predicting and simulating a virtual shape and size of the bar for asymmetric and symmetric patients. In conclusion, the i3DExcavatum allows preoperative personalization according to the thoracic morphology of each patient. It reduces surgery time and minimizes the margin error introduced by the manually bent bar, which only uses a template that copies the chest wall curvature.

Automatic modeling of an orthotic bracing for nonoperative correction of pectus carinatum

Pectus Carinatum is a deformity of the chest wall, characterized by an anterior protrusion of the sternum, often corrected surgically due to cosmetic motivation. This work presents an alternative approach to the current open surgery option, proposing a novel technique based on a personalized orthosis. Two different processes for the orthosis’ personalization are presented. One based on a 3D laser scan of the patient chest, followed by the reconstruction of the thoracic wall mesh using a radial basis function, and a second one, based on a computer tomography scan followed by a neighbouring cells algorithm. The axial position where the orthosis is to be located is automatically calculated using a Ray-Triangle intersection method, whose outcome is input to a pseudo Kochenek interpolating spline method to define the orthosis curvature. Results show that no significant differences exist between the patient chest physiognomy and the curvature angle and size of the orthosis, allowing a better cosmetic outcome and less initial discomfort.

Development of CBCT-based prostate setup correction strategies and impact of rectal distension.

BACKGROUND: Cone-beam computed tomography (CBCT) image-guided radiotherapy (IGRT) systems are widely used tools to verify and correct the target position before each fraction, allowing to maximize treatment accuracy and precision. In this study, we evaluate automatic three-dimensional intensity-based rigid registration (RR) methods for prostate setup correction using CBCT scans and study the impact of rectal distension on registration quality. METHODS: We retrospectively analyzed 115 CBCT scans of 10 prostate patients. CT-to-CBCT registration was performed using (a) global RR, (b) bony RR, or (c) bony RR refined by a local prostate RR using the CT clinical target volume (CTV) expanded with 1-to-20-mm varying margins. After propagation of the manual CT contours, automatic CBCT contours were generated. For evaluation, a radiation oncologist manually delineated the CTV on the CBCT scans. The propagated and manual CBCT contours were compared using the Dice similarity and a measure based on the bidirectional local distance (BLD). We also conducted a blind visual assessment of the quality of the propagated segmentations. Moreover, we automatically quantified rectal distension between the CT and CBCT scans without using the manual CBCT contours and we investigated its correlation with the registration failures. To improve the registration quality, the air in the rectum was replaced with soft tissue using a filter. The results with and without filtering were compared. RESULTS: The statistical analysis of the Dice coefficients and the BLD values resulted in highly significant differences (p<10(-6)) for the 5-mm and 8-mm local RRs vs the global, bony and 1-mm local RRs. The 8-mm local RR provided the best compromise between accuracy and robustness (Dice median of 0.814 and 97% of success with filtering the air in the rectum). We observed that all failures were due to high rectal distension. Moreover, the visual assessment confirmed the superiority of the 8-mm local RR over the bony RR. CONCLUSION: The most successful CT-to-CBCT RR method proved to be the 8-mm local RR. We have shown the correlation between its registration failures and rectal distension. Furthermore, we have provided a simple (easily applicable in routine) and automatic method to quantify rectal distension and to predict registration failure using only the manual CT contours.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.