Generating anatomical substructures for physically-based facial animation.

Physically-based facial animation techniques are capable of producing realistic facial deformations, but have failed to find meaningful use outside the academic community because they are notoriously difficult to create, reuse, and art-direct, in comparison to other methods of facial animation. This thesis addresses these shortcomings and presents a series of methods for automatically generating a skull, the superficial musculoaponeurotic system (SMAS – a layer of fascia investing and interlinking the mimic muscle system), and mimic muscles for any given 3D face model. This is done toward (the goal of) a production-viable framework or rig-builder for physically-based facial animation. This workflow consists of three major steps. First, a generic skull is fitted to a given head model using thin-plate splines computed from the correspondence between landmarks placed on both models. Second, the SMAS is constructed as a variational implicit or radial basis function surface in the interface between the head model and the generic skull fitted to it. Lastly, muscle fibres are generated as boundary-value straightest geodesics, connecting muscle attachment regions defined on the surface of the SMAS. Each step of this workflow is developed with speed, realism and reusability in mind

Automated color correction for colorimetric applications using barcodes

[eng] Color-based sensor devices often offer qualitative solutions, where a material change its color from one color to another, and this is change is observed by a user who performs a manual reading. These materials change their color in response to changes in a certain physical or chemical magnitude. Nowadays, we can find colorimetric indicators with several sensing targets, such as: temperature, humidity, environmental gases, etc. The common approach to quantize these sensors is to place ad hoc electronic components, e.g., a reader device. With the rise of smartphone technology, the possibility to automatically acquire a digital image of those sensors and then compute a quantitative measure is near. By leveraging this measuring process to the smartphones, we avoid the use of ad hoc electronic components, thus reducing colorimetric application cost. However, there exists a challenge on how-to acquire the images of the colorimetric applications and how-to do it consistently, with the disparity of external factors affecting the measure, such as ambient light conditions or different camera modules. In this thesis, we tackle the challenges to digitize and quantize colorimetric applications, such as colorimetric indicators. We make a statement to use 2D barcodes, well-known computer vision patterns, as the base technology to overcome those challenges. We focus on four main challenges: (I) to capture barcodes on top of real-world challenging surfaces (bottles, food packages, etc.), which are the usual surface where colorimetric indicators are placed; (II) to define a new 2D barcode to embed colorimetric features in a back-compatible fashion; (III) to achieve image consistency when capturing images with smartphones by reviewing existent methods and proposing a new color correction method, based upon thin-plate splines mappings; and (IV) to demonstrate a specific application use case applied to a colorimetric indicator for sensing CO2 in the range of modified atmosphere packaging, MAP, one of the common food-packaging standards.[cat] Els dispositius de sensat basats en color, normalment ofereixen solucions qualitatives, en aquestes solucions un material canvia el seu color a un altre color, i aquest canvi de color és observat per un usuari que fa una mesura manual. Aquests materials canvien de color en resposta a un canvi en una magnitud física o química. Avui en dia, podem trobar indicadors colorimètrics que amb diferents objectius, per exemple: temperatura, humitat, gasos ambientals, etc. L'opció més comuna per quantitzar aquests sensors és l'ús d'electrònica addicional, és a dir, un lector. Amb l'augment de la tecnologia dels telèfons intel·ligents, la possibilitat d'automatitzar l'adquisició d'imatges digitals d'aquests sensors i després computar una mesura quantitativa és a prop. Desplaçant aquest procés de mesura als telèfons mòbils, evitem l'ús d'aquesta electrònica addicional, i així, es redueix el cost de l'aplicació colorimètrica. Tanmateix, existeixen reptes sobre com adquirir les imatges de les aplicacions colorimètriques i de com fer-ho de forma consistent, a causa de la disparitat de factors externs que afecten la mesura, com per exemple la llum ambient or les diferents càmeres utilitzades. En aquesta tesi, encarem els reptes de digitalitzar i quantitzar aplicacions colorimètriques, com els indicadors colorimètrics. Fem una proposició per utilitzar codis de barres en dues dimensions, que són coneguts patrons de visió per computador, com a base de la nostra tecnologia per superar aquests reptes. Ens focalitzem en quatre reptes principals: (I) capturar codis de barres sobre de superfícies del món real (ampolles, safates de menjar, etc.), que són les superfícies on usualment aquests indicadors colorimètrics estan situats; (II) definir un nou codi de barres en dues dimensions per encastar elements colorimètrics de forma retro-compatible; (III) aconseguir consistència en la captura d'imatges quan es capturen amb telèfons mòbils, revisant mètodes de correcció de color existents i proposant un nou mètode basat en transformacions geomètriques que utilitzen splines; i (IV) demostrar l'ús de la tecnologia en un cas específic aplicat a un indicador colorimètric per detectar CO2 en el rang per envasos amb atmosfera modificada, MAP, un dels estàndards en envasos de menjar.

Directional Estimation for Robotic Beating Heart Surgery

In robotic beating heart surgery, a remote-controlled robot can be used to carry out the operation while automatically canceling out the heart motion. The surgeon controlling the robot is shown a stabilized view of the heart. First, we consider the use of directional statistics for estimation of the phase of the heartbeat. Second, we deal with reconstruction of a moving and deformable surface. Third, we address the question of obtaining a stabilized image of the heart

Use of Multicomponent Non-Rigid Registration to Improve Alignment of Serial Oncological PET/CT Studies

Non-rigid registration of serial head and neck FDG PET/CT images from a combined scanner can be problematic. Registration techniques typically rely on similarity measures calculated from voxel intensity values; CT-CT registration is superior to PET-PET registration due to the higher quality of anatomical information present in this modality. However, when metal artefacts from dental fillings are present in a pair of CT images, a nonrigid registration will incorrectly attempt to register the two artefacts together since they are strong features compared to the features that represent the actual anatomy. This leads to localised registration errors in the deformation field in the vicinity of the artefacts. Our objective was to develop a registration technique which overcomes these limitations by using combined information from both modalities. To study the effect of artefacts on registration, metal artefacts were simulated with one CT image rotated by a small angle in the sagittal plane. Image pairs containing these simulated artifacts were then registered to evaluate the resulting errors. To improve the registration in the vicinity where there were artefacts, intensity information from the PET images was incorporated using several techniques. A well-established B-splines based non-rigid registration code was reworked to allow multicomponent registration. A similarity measure with four possible weighted components relating to the ways in which the CT and PET information can be combined to drive the registration of a pair of these dual-valued images was employed. Several registration methods based on using this multicomponent similarity measure were implemented with the goal of effectively registering the images containing the simulated artifacts. A method was also developed to swap control point displacements from the PET-derived transformation in the vicinity of the artefact. This method yielded the best result on the simulated images and was evaluated on images where actual dental artifacts were present

Computer vision and optimization methods applied to the measurements of in-plane deformations

fi=vertaisarvioitu|en=peerReviewed

Applications of a Biomechanical Patient Model for Adaptive Radiation Therapy

Biomechanical patient modeling incorporates physical knowledge of the human anatomy into the image processing that is required for tracking anatomical deformations during adaptive radiation therapy, especially particle therapy. In contrast to standard image registration, this enforces bio-fidelic image transformation. In this thesis, the potential of a kinematic skeleton model and soft tissue motion propagation are investigated for crucial image analysis steps in adaptive radiation therapy. The first application is the integration of the kinematic model in a deformable image registration process (KinematicDIR). For monomodal CT scan pairs, the median target registration error based on skeleton landmarks, is smaller than (1.6 ± 0.2) mm. In addition, the successful transferability of this concept to otherwise challenging multimodal registration between CT and CBCT as well as CT and MRI scan pairs is shown to result in median target registration error in the order of 2 mm. This meets the accuracy requirement for adaptive radiation therapy and is especially interesting for MR-guided approaches. Another aspect, emerging in radiotherapy, is the utilization of deep-learning-based organ segmentation. As radiotherapy-specific labeled data is scarce, the training of such methods relies heavily on augmentation techniques. In this work, the generation of synthetically but realistically deformed scans used as Bionic Augmentation in the training phase improved the predicted segmentations by up to 15% in the Dice similarity coefficient, depending on the training strategy. Finally, it is shown that the biomechanical model can be built-up from automatic segmentations without deterioration of the KinematicDIR application. This is essential for use in a clinical workflow