Jean Cousty

VOIDD: automatic vessel of intervention dynamic detection in PCI procedures

In this article, we present the work towards improving the overall workflow of the Percutaneous Coronary Interventions (PCI) procedures by capacitating the imaging instruments to precisely monitor the steps of the procedure. In the long term, such capabilities can be used to optimize the image acquisition to reduce the amount of dose or contrast media employed during the procedure. We present the automatic VOIDD algorithm to detect the vessel of intervention which is going to be treated during the procedure by combining information from the vessel image with contrast agent injection and images acquired during guidewire tip navigation. Due to the robust guidewire tip segmentation method, this algorithm is also able to automatically detect the sequence corresponding to guidewire navigation. We present an evaluation methodology which characterizes the correctness of the guide wire tip detection and correct identification of the vessel navigated during the procedure. On a dataset of 2213 images from 8 sequences of 4 patients, VOIDD identifies vessel-of-intervention with accuracy in the range of 88% or above and absence of tip with accuracy in range of 98% or above depending on the test case.

Watershed Cuts: Thinnings, Shortest Path Forests, and Topological Watersheds

We recently introduced watershed cuts, a notion of watershed in edge-weighted graphs. In this paper, our main contribution is a thinning paradigm from which we derive three algorithmic watershed cut strategies: The first one is well suited to parallel implementations, the second one leads to a flexible linear-time sequential implementation, whereas the third one links the watershed cuts and the popular flooding algorithms. We state that watershed cuts preserve a notion of contrast, called connection value, on which several morphological region merging methods are (implicitly) based. We also establish the links and differences between watershed cuts, minimum spanning forests, shortest path forests, and topological watersheds. Finally, we present illustrations of the proposed framework to the segmentation of artwork surfaces and diffusion tensor images.

Segmentation of 4D cardiac MRI: Automated method based on spatio-temporal watershed cuts

Based on discrete mathematical morphology, we introduce in this paper a new watershed framework which allows for segmenting spatio-temporal images, that we apply to medical image analysis. Specifically, we propose a new automated and fast procedure to segment the left ventricular myocardium in 4D (3D+t) cine-MRI sequences. Both quantitative and qualitative evaluation are provided. Thanks to the comparison with manual segmentation performed by two cardiologists, we demonstrate the accuracy of the proposed method. The relevance of the ejection fraction and myocardium mass measured from segmentations is also assessed. Furthermore, we show that the proposed 4D procedure allows to keep the temporal coherency between the successive 3D segmentations obtained along the time sequence. In an effort to promote open science, both the data and the software are available on-line.

Some Morphological Operators in Graph Spaces

We study some basic morphological operators acting on the lattice of all subgraphs of a (non-weighted) graph

Incremental algorithm for hierarchical minimum spanning forests and saliency of watershed cuts

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Morphological filtering on graphs

. To this end, we consider two dual adjunctions between the edge set and the vertex set of

Automated, accurate and fast segmentation of 4D cardiac MR images

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Playing with Kruskal: Algorithms for Morphological Trees in Edge-Weighted Graphs

. This allows us (i) to recover the classical notion of a dilation/erosion of a subset of the vertices of

A hierarchical image segmentation algorithm based on an observation scale

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Constructive Links between Some Morphological Hierarchies on Edge-Weighted Graphs

and (ii) to extend it to subgraphs of