Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Assessment of 3D scanners for modeling Pectus Carinatum corrective bar

Pectus Carinatum (PC) is a chest deformity consisting on the anterior protrusion of the sternum and adjacent costal cartilages. Non-operative corrections, such as the orthotic compression brace, require previous information of the patient chest surface, to improve the overall brace fit. This paper focuses on the validation of the Kinect scanner for the modelling of an orthotic compression brace for the correction of Pectus Carinatum. To this extent, a phantom chest wall surface was acquired using two scanner systems – Kinect and Polhemus FastSCAN – and compared through CT. The results show a RMS error of 3.25mm between the CT data and the surface mesh from the Kinect sensor and 1.5mm from the FastSCAN sensor

Real-time 3D interactive segmentation of echocardiographic data through user-based deformation of B-spline explicit active surfaces

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.

A importância da personagem virtual no contexto da animação 3D em tempo real

O desenvolvimento de personagens digitais tridimensionais1 na área da animação, a constante procura por soluções tecnológicas convincentes, aliado a uma estética própria, tem contribuído para o sucesso e afirmação da animação tridimensional, na indústria do entretenimento. Contudo, toda a obra que procura ou explora a vertente digital/3D, torna-se ‘vitima’ das limitações do render2 aplicado a uma sequência de imagens, devido ao aumento dos custos financeiros e humanos, assim como da influência e dificuldade implicadas no cumprimento dos objectivos e prazos. O tempo real tem assumido, cada vez mais, um papel predominante na indústria da animação interactiva. Com a evolução da tecnologia surgiu a necessidade de procurar a metodologia apropriada que sirva de alavanca para o desenvolvimento de animações 3D em tempo real, através de softwares open-source ou de baixo orçamento, para a redução de custos, que possibilite simultaneamente descartar qualquer dependência do render na animação 3D. O desenvolvimento de personagens em tempo real, possibilita o surgimento de uma nova abordagem: a interactividade na arte de animar. Esta possibilita a introdução de um vasto leque de novas aplicações e consequentemente, contribui para o aumento do interesse e curiosidade por parte do espectador. No entanto, a inserção, implementação e (ab)uso da tecnologia na área da animação, levanta questões atuais sobre qual o papel do animador. Esta dissertação procura analisar estes aspectos, dando apoio ao projecto de animação 3D em tempo real, denominado ‘PALCO’.

Capacidad de enraizamiento de plantas matrices promisorias de Myrciaria dubia (Kunth) Mc Vaugh en cámaras de subirrigación¹

Camu camu es una fruta nativa de la Amazonía, que llama la atención por el alto contenido de vitamina C (6,116 mg/ 100 g de pulpa), está en proceso de domesticación, por lo cual se está investigando un método de propagación vegetativa que permita avanzar en el proceso de mejoramiento genético. El objetivo de este trabajo fue evaluar la capacidad rizogénica de plantas matrices promisorias de camu camu "Myrciaria dubia (Kunth) McVaugh" según el aumento del número de hojas, mediante la técnica de estacas herbáceas en cámaras de subirrigación. El ensayo fue conducido mediante un Diseño de Bloques Completamente al Azar (DBCA) con arreglo factorial 9Ax3B, con 3 repeticiones y 15 estacas por unidad experimental. El factor A, estuvo constituido por nueve plantas matrices y el factor B: pares de hojas con 3 niveles: 1; 2 y 3 pares. El enraizamiento fue evaluado después de 90 días. Se observó que existió interacción estadística significativa para las variables: porcentaje de enraizamiento, longitud y número de raíces. Para las variables porcentaje de callo y porcentaje de mortalidad se encontró efecto de la planta matriz y pares de hojas. Los resultados muestran que el porcentaje de enraizamiento estuvo influenciado por efectos intrínsecos adherentes a la variabilidad genotípica de las plantas matrices, presentando un alto grado de dispersión, que osciló entre 91,11 % y 0,00 %, mostrando una alta variabilidad y marcada influencia de la planta matriz sobre el proceso de rizogénesis, influyendo de manera altamente significativa en el enraizamiento. Con respecto al área foliar, estacas con 2 y 3 pares de hojas, independiente de la planta matriz, presentaron mayor capacidad de enraizamiento. Con base en estos resultados se concluye que el efecto de la variabilidad genotípica y el área foliar influyen de manera altamente significativa en el proceso de rizogénesis de estacas herbáceas de camu camu.

Assessment of 3D scanners for modeling pectus carinatum corrective bar

Pectus Carinatum (PC) is a chest deformity consisting on the anterior protrusion of the sternum and adjacent costal cartilages. Non-operative corrections, such as the orthotic compression brace, require previous information of the patient chest surface, to improve the overall brace fit. This paper focuses on the validation of the Kinect scanner for the modelling of an orthotic compression brace for the correction of Pectus Carinatum. To this extent, a phantom chest wall surface was acquired using two scanner systems – Kinect and Polhemus FastSCAN – and compared through CT. The results show a RMS error of 3.25mm between the CT data and the surface mesh from the Kinect sensor and 1.5mm from the FastSCAN sensor.

Palco: a multisensor realtime 3D cartoon production system

This paper presents Palco, a prototype system specifically designed for the production of 3D cartoon animations. The system addresses the specific problems of producing cartoon animations, where the main obj ective is not to reproduce realistic movements, but rather animate cartoon characters with predefined and characteristic body movements and facial expressions. The techniques employed in Palco are simple and easy to use, not requiring any invasive or complicated motion capture system, as both body motion and facial expression of actors are captured simultaneously, using an infrared motion detection sensor, a regular camera and a pair of electronically instrumented gloves. The animation process is completely actor-driven, with the actor controlling the character movements, gestures, facial expression and voice, all in realtime. The actor controlled cartoonification of the captured facial and body motion is a key functionality of Palco, and one that makes it specifically suited for the production of cartoon animations.

Semi-automatic 3D Segmentation Of Costal Cartilage In CT Data From Pectus Excavatum Patients

One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.

Assessment of Laparoscopic Skills Performance: 2D Versus 3D Vision and Classic Instrument Versus New Hand-Held Robotic Device for Laparoscopy

Introduction and Objectives. Laparoscopic surgery has undeniable advantages, such as reduced postoperative pain, smaller incisions, and faster recovery. However, to improve surgeons’ performance, ergonomic adaptations of the laparoscopic instruments and introduction of robotic technology are needed. The aim of this study was to ascertain the influence of a new hand-held robotic device for laparoscopy (HHRDL) and 3D vision on laparoscopic skills performance of 2 different groups, naïve and expert. Materials and Methods. Each participant performed 3 laparoscopic tasks—Peg transfer, Wire chaser, Knot—in 4 different ways. With random sequencing we assigned the execution order of the tasks based on the first type of visualization and laparoscopic instrument. Time to complete each laparoscopic task was recorded and analyzed with one-way analysis of variance. Results. Eleven experts and 15 naïve participants were included. Three-dimensional video helps the naïve group to get better performance in Peg transfer, Wire chaser 2 hands, and Knot; the new device improved the execution of all laparoscopic tasks (P < .05). For expert group, the 3D video system benefited them in Peg transfer and Wire chaser 1 hand, and the robotic device in Peg transfer, Wire chaser 1 hand, and Wire chaser 2 hands (P < .05). Conclusion. The HHRDL helps the execution of difficult laparoscopic tasks, such as Knot, in the naïve group. Three-dimensional vision makes the laparoscopic performance of the participants without laparoscopic experience easier, unlike those with experience in laparoscopic procedures.

Análise da aplicação de um sistema domótico no desempenho térmico de frações autónomas de habitação face ao sistema de certificação energética: casos de estudo

A presente dissertação tem por finalidade compreender as vantagens da aplicação da domótica no comportamento energético de uma fração habitacional, e possível efeito na classificação energética do Sistema de Certificação Energética (SCE), tendo assentado na realização de simulações dinâmicas cuja modelação foi feita no software DesignBuilder, associado ao software EnergyPlus, na parte respeitante aos cálculos. Como forma de melhorar a qualidade de vida, reduzir o trabalho doméstico, aumentar o bem-estar e a segurança, foi criada a domótica que é responsável pela automação predial. O conceito de automação implica a integração da iluminação, eletrodomésticos, ar-condicionado, controlo de acessos, alarmes, sensores e sistemas de dados, voz e imagem de um edifício ou de uma fração autónoma, fazendo com que todos os seus componentes possam realizar ações em conjunto a fim de facilitar a vida dos seus utilizadores. A preocupação com a segurança, a gestão e o controlo, a redução de custos e o bem-estar trouxe os sistemas de automação para a sociedade. Esses sistemas divididem-se em dois grandes grupos: os subsistemas de supervisão e controlo das utilidades, que realizam o controlo das instalações elétricas, de arrefecimento e aquecimento, de instalações hidráulicas (águas sanitárias), de gás e o controle de elevadores; e os subsistemas de segurança, de proteção contra incêndio, contra intrusão e a monitorização visual centralizada (câmaras de vídeo-vigilância). Na construção de um edifício existe a preocupação cada vez maior na garantia do conforto aliado ao menor consumo de energia possível, isto é, a temperatura e a iluminação adequada para a realização de diferentes tarefas a efetuar, sem que implique um maior consumo. A regulação da temperatura interior da habitação, o controlo de luzes através de sensores e abertura de fecho dos dispositivos de sombreamento (persianas), através de domótica, permitirá o maior proveito da iluminação natural e a temperatura aos utilizadores da fracção em cada instante. Com tudo o que a domótica permite é necessário saber quais as vantagens e desvantagens na sua implementação. Com esta finalidade, realizou-se a análise baseada no RCCTE, de três apartamentos de um edifício, com a mesma tipologia mas com distintas orientações de envidraçados. Os apartamentos escolhidos no último piso do edifício. Posteriormente , optou-se por uma das fracções para o aprofundamento da análise e avaliação de implementação de sistemas domóticos de contolo de abertura/e fecho de dispositivos de oclusão de vãos para controlo dos ganhos solares e abertura e fecho dos vãos envidraçados para controlar as cargas térmicas por ventilação. Neste intuito, desenvolveu-se um modelo 3D com recurso ao software DesignBuilder, Energy Plus, em diferentes zonas climáticas, em regime dinâmico, por forma a contabilizar a diferença entre os fatores que não são quantificados através da análise feita pelo RCCTE. Após uma análise com as permissas incluídas no RCCTE (ventilação e factor solar), é imposto no DesignBuilder alguns aspetos da domótica, como a abertura/fecho de persianas/janelas obtendo-se para cada situação as perdas e ganhos através de cada elemento (envidraçados, necessidades de aquecimento e arrefecimento). Foi ainda elaborado um pequeno estudo da viabilidade económica da implementação de um sistema domótico.

Caminhamento fotogramétrico com arranjo triangular de câmaras fotográficas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Contributo para a utilização segura de câmaras de segurança biológica na manipulação de medicamentos citotóxicos

Mestrado em Segurança e Higiene do Trabalho.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.