Automatical vessel wall detection in intravascular coronary OCT

Tung, Kai-Pin; Shi, Wenzhe; Silva, Ranil de; Edwards, Eddie; Rueckert, Daniel

doi:10.1109/isbi.2011.5872481

Cited by 25 publications

(32 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Como foi discutido anteriormente, a literatura mostra alguns enfoques computacionais para a segmentação do lúmen na coronária em imagens IOCT (Dubuisson et al, 2009;Gurmeric et al, 2009;Sihan et al, 2008;Tsantis et al, 2012;Tung et al, 2011). Contudo, apesar dos esforços, a ausência de um número razoável de métodos, e resultados mais acurados dos mesmos, faz com que a procura de métodos alternativos de segmentação da coronária continue.…”

Section: Discussionunclassified

“…Comparando com a literatura, Tsantis et al (2012) oferece um método de segmentação automática do lúmen para imagens da artéria femoral com um valor de overlap de 93,7 ± 4,5, eficácia quase 3% inferior ao da nossa proposta. Em Tung et al (2011) a segmentação automática do lúmen de coronárias é feita obtendo um valor médio de Overlap DICE de 97,25 ± 2,0, o qual é relevante, mas ainda inferior ao obtido neste trabalho. Finalmente, na comparação com os métodos já publicados, podemos ver que o método proposto aqui apresentou resultados melhores do que os da literatura.…”

Section: Discussionunclassified

“…No trabalho de Tung et al (2011), os autores fazem a segmentação do lúmen da coronária utilizando uma combinação de um algoritmo de maximização de Expectativa (Dempster et al, 1977), um algoritmo Graph Cuts (Boykov e Jolly, 2001) e contornos ativos (Kass et al, 1988). No método proposto por Gurmeric et al (2009), os pesquisadores utilizam contornos ativos que se propagam com equação diferencial ordinária (EDO) para atingir uma ótima solução.…”

Section: Introductionunclassified

See 2 more Smart Citations

Segmentação do lúmen em imagens de IOCT usando Fuzzy Connectedness e Reconstrução Binária Morfológica

Cárdenas

Moraes

Furuie

2013

RBEB

View full text Add to dashboard Cite

Section: Discussionunclassified

Section: Introductionunclassified

See 1 more Smart Citation

Segmentação do lúmen em imagens de IOCT usando Fuzzy Connectedness e Reconstrução Binária Morfológica

Cárdenas

Moraes

Furuie

2013

RBEB

View full text Add to dashboard Cite

“…1 Automated assessment can reduce this error and produce more consistent image interpretation. Various techniques have been reported for lumen segmentation, [1][2][3][4][5][6][7][8] stent strut detection, 7 and plaque characterization. 1,9 These approaches are either semi or fully automated.…”

Section: Introductionmentioning

confidence: 99%

“…7 Alternatively, a combination approach with expectation maximization (EM) for labeling and graph-cut for lumen segmentation has been reported. 8 All these techniques use the tissue region as the reference from which to determine the boundary. The lumen geometry generated can then be refined using an active contour method (ACM).…”

Section: Introductionmentioning

confidence: 99%

Automatic segmentation of coronary morphology using transmittance-based lumen intensity-enhanced intravascular optical coherence tomography images and applying a localized level-set-based active contour method

2016

View full text Add to dashboard Cite

, "Automatic segmentation of coronary morphology using transmittance-based lumen intensity-enhanced intravascular optical coherence tomography images and applying a localized level-set-based active contour method," J. Abstract. Lumen segmentation from clinical intravascular optical coherence tomography (IV-OCT) images has clinical relevance as it provides a full three-dimensional perspective of diseased coronary artery sections. Inaccurate segmentation may occur when there are artifacts in the image, resulting from issues such as inadequate blood clearance. This study proposes a transmittance-based lumen intensity enhancement method that ensures only lumen regions are highlighted. A level-set-based active contour method that utilizes the local speckle distribution properties of the image is then employed to drive an image-specific active contour toward the true lumen boundaries. By utilizing local speckle properties, the intensity variation issues within the image are resolved. This combined approach has been successfully applied to challenging clinical IV-OCT datasets that contains multiple lumens, residual blood flow, and its shadowing artifact. A method to identify the guide-wire and interpolate the lost lumen segments has been implemented. This approach is fast and can be performed even when guide-wire boundaries are not easily identified. Lumen enhancement also makes it easy to identify vessel side branches. This automated approach is not only able to extract the arterial lumen, but also the smaller microvascular lumens that are associated with the vasa vasorum and with atherosclerotic plaque.

show abstract

Combining region‐based and imprecise boundary‐based cues for interactive medical image segmentation

Jones

Xie

Essa

2014

Numer Methods Biomed Eng

View full text Add to dashboard Cite

In this paper, we present an approach combining both region selection and user point selection for user-assisted segmentation as either an enclosed object or an open curve, investigate the method of image segmentation in specific medical applications (user-assisted segmentation of the media-adventitia border in intravascular ultrasound images, and lumen border in optical coherence tomography images), and then demonstrate the method with generic images to show how it could be utilized in other types of medical image and is not limited to the applications described. The proposed method combines point-based soft constraint on object boundary and stroke-based regional constraint. The user points act as attraction points and are treated as soft constraints rather than hard constraints that the segmented boundary has to pass through. The user can also use strokes to specify region of interest. The probabilities of region of interest for each pixel are then calculated, and their discontinuity is used to indicate object boundary. The combinations of different types of user constraints and image features allow flexible and robust segmentation, which is formulated as an energy minimization problem on a multilayered graph and is solved using a shortest path search algorithm. We show that this combinatorial approach allows efficient and effective interactive segmentation, which can be used with both open and closed curves to segment a variety of images in different ways. The proposed method is demonstrated in the two medical applications, that is, intravascular ultrasound and optical coherence tomography images, where image artefacts such as acoustic shadow and calcification are commonplace and thus user guidance is desirable. We carried out both qualitative and quantitative analysis of the results for the medical data; comparing the proposed method against a number of interactive segmentation techniques.

show abstract

Automatical vessel wall detection in intravascular coronary OCT

Cited by 25 publications

References 12 publications

Segmentação do lúmen em imagens de IOCT usando Fuzzy Connectedness e Reconstrução Binária Morfológica

Segmentação do lúmen em imagens de IOCT usando Fuzzy Connectedness e Reconstrução Binária Morfológica

Automatic segmentation of coronary morphology using transmittance-based lumen intensity-enhanced intravascular optical coherence tomography images and applying a localized level-set-based active contour method

Combining region‐based and imprecise boundary‐based cues for interactive medical image segmentation

Contact Info

Product

Resources

About