3 research outputs found
Non-rigid medical image registration with extended free form deformations: modelling general tissue transitions
Image registration seeks pointwise correspondences between the same or analogous objects in different images. Conventional registration methods generally impose continuity and smoothness throughout the image. However, there are cases in which the deformations may involve discontinuities. In general, the discontinuities can be of different types, depending on the physical properties of the tissue transitions involved and boundary conditions. For instance, in the respiratory motion the lungs slide along the thoracic cage following the tangential direction of their interface. In the normal direction, however, the lungs and the thoracic cage are constrained to be always in contact but they have different material properties producing different compression or expansion rates. In the literature, there is no generic method, which handles different types of discontinuities and considers their directional dependence.
The aim of this thesis is to develop a general registration framework that is able to correctly model different types of tissue transitions with a general formalism. This has led to the development of the eXtended Free Form Deformation (XFFD) registration method. XFFD borrows the concept of the interpolation method from the eXtended Finite Element method (XFEM) to incorporate discontinuities by enriching B-spline basis functions, coupled with extra degrees of freedom. XFFD can handle different types of discontinuities and encodes their directional-dependence without any additional constraints.
XFFD has been evaluated on digital phantoms, publicly available 3D liver and lung CT images. The experiments show that XFFD improves on previous methods and that it is important to employ the correct model that corresponds to the discontinuity type involved at the tissue transition. The effect of using incorrect models is more evident in the strain, which measures mechanical properties of the tissues
Cardiac motion and deformation estimation in tagged magnetic resonance imaging
Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Electrónica Médica)Cardiovascular diseases are the main cause of death in Europe, with an estimate
of 4.3 million deaths each year. The assessment of the regional wall deformation is a
relevant clinical indicator, and can be used to detect several cardiac lesions. Nowadays,
this study can be performed using several image modalities. In the current thesis, we
focus on tagged Magnetic Resonance imaging (t-MRI) technique. Such technique
allows acquiring images with tags on the myocardium, which deform with the muscle.
The present thesis intends to assess the left ventricle (LV) deformation using
radial and circumferential strain. To compute such strain values, both endo- and
epicardial contours of the LV are required.
As such, a new framework to automatically assess the LV function is proposed.
This framework presents: (i) an automatic segmentation technique, based on a tag
suppression strategy followed by an active contour segmentation method, and (ii) a
tracking approach to extract myocardial deformation, based on a non-rigid registration
method. The automatic segmentation uses the B-spline Explicit Active Surface
framework, which was previously applied in ultra-sound and cine-MRI images. In both
cases, a real-time and accurate contour was achieved. Regarding the registration step,
starting from a state-of-art approach, termed sequential 2D, we suggest a new method
(termed sequential 2D+t), where the temporal information is included on the model.
The tracking methods were first tested on synthetic data to study the registration
parameters influence. Furthermore, the proposed and original methods were applied on
porcine data with myocardial ischemia. Both methods were able to detect dysfunctional
regions. A comparison between the strain curve in the sequential 2D and sequential
2D+t strategies was also shown. As conclusion, a smoothing effect in the strain curve
was detected in the sequential 2D+t strategy. The validation of the segmentation
approach uses a human dataset. A comparison between the manual contour and the
proposed segmentation method results was performed. The results, suggest that
proposed method has an acceptable performance, removing the tedious task related with
manual segmentation and the intra-observer variability. Finally, a comparison between
the proposed framework and the currently available commercial software was
performed. The commercial software results were obtained from core-lab analysis. An
acceptable result (r = 0.601) was achieved when comparing the strain peak values.
Importantly, the proposed framework appears to present a more acceptable result.As doenças cardiovasculares são a principal causa de morte na Europa, com
aproximadamente 4.7 milhões de mortes por ano. A avaliação da deformação do
miocárdio a um nível local é um importante indicador clínico e pode ser usado para a
deteção de lesões cardíacas. Este estudo é normalmente realizado usando várias
modalidades de imagem médica. Nesta tese, a Resonância Magnética (RM) marcada foi
a técnica selecionada. Estas imagens têm marcadores no músculo cardíaco, os quais se
deformam com o miocárdio e podem ser usados para o estudo da deformação cardíaca.
Nesta tese, pretende-se estudar a deformação radial e circunferencial do
ventrículo esquerdo (VE). Assim, um contorno do endo- e epicárdio no VE é essencial.
Desta forma, uma ferramenta para o estudo da deformação do VE foi
desenvolvida. Esta possui: (i) um método de segmentação automático, usando uma
estratégia de supressão dos marcadores, seguido de uma segmentação c um contorno
ativo, e (ii) um método de tracking para determinação da deformação cardíaca, baseado
em registo não rígido. A segmentação automática utiliza a ferramenta B-spline Explicit
Active Surface, que foi previamente aplicada em imagens de ultrassons e cine-RM. Em
ambos os casos, uma segmentação em tempo real e com elevada exatidão foi alcançada.
Vários esquemas de registo foram apresentados. Neste ponto, começando com uma
técnica do estado da arte (designada de sequencial 2D), uma nova metodologia foi
proposta (sequencial 2D+t), onde a informação temporal é incorporada no modelo.
De forma a analisar a influência dos parâmetros do registo, estes foram
estudados num dataset sintético. De seguida, os diferentes esquemas de registo foram
testados num dataset suíno com isquemia. Ambos os métodos foram capazes de detetar
as regiões disfuncionais. De igual forma, utilizando as curvas de deformação obtidas
para cada um dos métodos propostos, foi possível observar uma suavização na direção
temporal para o método sequencial 2D+t. Relativamente à segmentação, esta foi
validada com um dataset humano. Um contorno manual foi comparado com o obtido
pelo método proposto. Os resultados sugerem que a nova estratégia é aceitável, sendo
mais rápida do que a realização de um contorno manual e eliminando a variabilidade
entre observadores. Por fim, realizou-se uma comparação entre a ferramenta proposta e
um software comercial (com análise de core-lab). A comparação entre os valores de
pico da deformação exibe uma correlação plausível (r=0.601). Contudo, é importante
notar, que a nova ferramenta tende a apresentar um resultado mais aceitável