Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains. We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in MRI. We replace the manual interaction with a robust EM-based approach in order to discriminate between MS lesions and the Normal Appearing Brain Tissues (NABT). Evaluation is performed ...

In this paper, we propose an interactive method for lung nodule segmentation. Given a seed point, the segmentation process consisting of three steps is done automatically. The first step is intensity normalization. The second one is to build an energy function for graph cuts. The third one is to do the segmentation by graph cuts. In the third step, if there are imperfects in the result, we prov...

This paper presents a multiresolutional brain extraction framework which utilizes graph cuts technique to classify head magnetic resonance (MR) images into brain and non-brain regions. Starting with an over-extracted brain region, we refine the segmentation result by trimming non-brain regions in a coarse-to-fine manner. The extracted brain at the coarser level will be propagated to the finer l...

These are notes on the method of normalized graph cuts and its applications to graph clustering. I provide a fairly thorough treatment of this deeply original method due to Shi and Malik, including complete proofs. I include the necessary background on graphs and graph Laplacians. I then explain in detail how the eigenvectors of the graph Laplacian can be used to draw a graph. This is an attrac...

C-V model can self-adapt to the changes of curve topology but requires more iterations and needs more computing time. Graph cuts algorithm is good at getting the global optimum in a short time but not suitable for concave object extraction. To overcome the flaws of these two algorithms, an optimized iteration algorithm has been proposed. First the initial contour is deformed with an improved C-...

Segmentation of coronary arteries in angiography images is a fundamental tool to evaluate arterial diseases and choose proper coronary treatment. The accurate segmentation of coronary arteries has become an important topic for the registration of different modalities, which allows physicians rapid access to different medical imaging information from Computed Tomography (CT) scans or Magnetic Re...

In technology mapping, enumeration of subcircuits or cuts to be replaced by a standard cell is an important step that decides both the quality of the solution and execution speed. In this work, we view cuts as set of edges instead of as set of nodes and based on it, provide a classification of cuts. It is shown that if enumeration is restricted to a subclass of cuts called unidirectional cuts, ...

We present a fully automatic segmentation method to extract media-adventitia border in IVUS images with shape prior information. Segmentation of IVUS has shown to be an intricate process due to relatively low contrast and various forms of interferences and artefacts caused by, for instance, calcification and acoustic shadow. We incorporate shape prior with an automatic graph cut technique to pr...

INTERACTIVE PART SELECTION FOR MESH AND POINT MODELS USING HIERARCHICAL GRAPH-CUT PARTITIONING Steven W. Brown Department of Computer Science Master of Science This thesis presents a method for interactive part selection for mesh and point set surface models that combines scribble-based selection methods with hierarchically accelerated graph-cut segmentation. Using graph-cut segmentation to det...

A new method for motion segmentation based on reference motion layer mosaics is presented. We assume that the scene is composed of a set of layers whose motion is well described by parametric models. This usual assumption is compatible with the notion of motion layer mosaic, which allows a compact representation of the sequence with a small number of mosaics only. We segment the sequence using ...