3 research outputs found
Fully automatic left ventricular myocardial strain estimation in 2D short-axis tagged magnetic resonance imaging
Cardiovascular diseases are among the leading causes of death and frequently result in local myocardial dysfunction. Among the numerous imaging modalities available to detect these dysfunctional regions, cardiac deformation imaging through tagged magnetic resonance imaging (t-MRI) has been an attractive approach. Nevertheless, fully automatic analysis of these data sets is still challenging. In this work, we present a fully automatic framework to estimate left ventricular myocardial deformation from t-MRI. This strategy performs automatic myocardial segmentation based on B-spline explicit active surfaces, which are initialized using an annular model. A non-rigid image-registration technique is then used to assess myocardial deformation. Three experiments were set up to validate the proposed framework using a clinical database of 75 patients. First, automatic segmentation accuracy was evaluated by comparing against manual delineations at one specific cardiac phase. The proposed solution showed an average perpendicular distance error of 2.35 +/- 1.21 mm and 2.27 +/- 1.02 mm for the endo- and epicardium, respectively. Second, starting from either manual or automatic segmentation, myocardial tracking was performed and the resulting strain curves were compared. It is shown that the automatic segmentation adds negligible differences during the strain-estimation stage, corroborating its accuracy. Finally, segmental strain was compared with scar tissue extent determined by delay-enhanced MRI. The results proved that both strain components were able to distinguish between normal and infarct regions. Overall, the proposed framework was shown to be accurate, robust, and attractive for clinical practice, as it overcomes several limitations of a manual analysis.FCT—Fundacão para a Ciência e a Tecnologia, Portugal, and the European Social Found, European Union, for funding support through the Programa Operacional Capital Humano (POCH) in the scope of the PhD grants SFRH/BD/95438/2013 (P Morais) and SFRH/BD/93443/2013 (S Queirós). This work was supported by the projects NORTE-07-0124-FEDER-000017 and NORTE-01-0145-FEDER-000013, co-funded by Programa Operacional Regional do Norte, Quadro de Referência Estratégico Nacional, through Fundo Europeu de Desenvolvimento Regional (FEDER). The authors would also like to acknowledge the EU (FP7) framework program, for the financial support of the DOPPLER-CIP project (grant no. 223615)info:eu-repo/semantics/publishedVersio
Fast Fully Automatic Segmentation of the Myocardium in 2D cine MR Images
International audienceA novel automatic initialization procedure for left ventricle (LV) cardiac magnetic resonance (CMR) segmentation is proposed through the combination of a LV localization method based on multilevel Otsu thresholding and an elliptical annular template matching algorithm. We then propose to adapt the recent B-spline Explicit Active Surfaces (BEAS) framework to the properties of CMR images by integrating two dedicated energy terms: a weighted localized Chan-Vese region-based energy to explicitly control the equilibrium point between the two regions around each interface and a combined local and global region-based formulation for the myocardial region. The proposed method has been validated on 45 mid-ventricular images taken from the 2009 MICCAI LV segmentation challenge. Results show the efficiency of our method both in terms of shape accuracy and computational times
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 nÃvel local é um importante indicador clÃnico e pode ser usado para a
deteção de lesões cardÃacas. 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 cardÃaco, os quais se
deformam com o miocárdio e podem ser usados para o estudo da deformação cardÃaca.
Nesta tese, pretende-se estudar a deformação radial e circunferencial do
ventrÃculo 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 cardÃaca, baseado
em registo não rÃgido. 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 suÃno 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 possÃvel 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 plausÃvel (r=0.601). Contudo, é importante
notar, que a nova ferramenta tende a apresentar um resultado mais aceitável