Felipe P. G. Bergo

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The absence of object information very often asks for considerable human assistance in medical image segmentation. Many interactive two-dimensional and three-dimensional (3-D) segmentation methods have been proposed, but their response time to user's actions should be considerably reduced to make them viable from the practical point of view. We circumvent(More)
The Image Foresting Transform (IFT) is a tool for the design of image processing operators based on con-nectivity, which reduces image processing problems into an optimum-path forest problem in a graph derived from the image. A new image operator is presented, which solves segmentation by pruning trees of the forest. An IFT is applied to create an(More)
Image segmentation using tree pruning (TP) and watershed (WS) has been presented in the framework of the image forest transform (IFT) - a method to reduce image processing problems related to connectivity into an optimum-path forest problem in a graph. Given that both algorithms use the IFT with similar parameters, they usually produce similar segmentation(More)
Although Friedreich’s ataxia is characterized by spinal cord atrophy, it remains to be investigated the possible correlation of such atrophy with clinical disability and genetic parameters. Thirty-three patients with Friedreich’s ataxia and 30 healthy controls underwent MRI on a 3 T scanner. We used T1-weighted 3D images to estimate spinal cord area and(More)
The notion of " strength of connectedness " between pixels has been successfully used in image segmentation. We present extensions to these works, which can considerably improve the efficiency of object delineation tasks. A set of pixels is said to be a κ-connected component with respect to a seed pixel, when the strength of connectedness of any pixel in(More)
The image foresting transform (IFT) has been proposed for the design of image operators based on connectivity. The IFT reduces image processing problems into a minimum-cost path forest problem in a graph derived from the image. It has been successfully used for image filtering, segmentation, and analysis. In this work, we propose a novel image operator(More)
Focal cortical dysplasia is the most common malformation in patients with intractable epilepsy. The segmentation of FCD lesions in MR-T1 images of the brain is a crucial step for treatment planning. In this work we present a new FCD segmentation technique based on analysis of texture asymmetry. This technique does not rely on template-based segmen-tation(More)