Publications de Engin Türetken

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Reconstructing complex curvilinear structures such as neural circuits, road networks, and blood vessels is a key challenge in many scientific and engineering fields. It has a broad range of applications, from the delineation of micrometer-sized neurons in ...

The problem of estimating a surface shape from its observed reflectance properties still remains a challenging task in computer vision. The presence of global illumination effects such as inter-reflections or cast shadows makes the task particularly diffic ...

This document describes an ITK implementation of an interactive method for tracing curvilinear structures. The basic tools provided in this framework are an oriented flux-based tubularity measure and a geodesic path tracer that uses the fast marching algor ...

We propose an approach to reconstructing tree structures that evolve over time in 2D images and 3D image stacks such as neuronal axons or plant branches. Instead of reconstructing structures in each image independently, we do so for all images simultaneous ...

Although tracing linear structures in 2D images and 3D image stacks has received much attention over the years, full automation remains elusive. In this paper, we formulate the delineation problem as one of solving a Quadratic Mixed Integer Program (Q-MIP) ...

We present a novel approach to fully automated delineation of tree structures in noisy 2D images and 3D image stacks. Unlike earlier methods that rely mostly on local evidence, our method builds a set of candidate trees over many different subsets of point ...

We present a novel probabilistic approach to fully automated delineation of tree structures in noisy 2D images and 3D image stacks. Unlike earlier methods that rely mostly on local evidence, ours builds a set of candidate trees over many different subsets ...

Finding the centerline and estimating the radius of linear structures is a critical first step in many applications, ranging from road delineation in 2D aerial images to modeling blood vessels, lung bronchi, and dendritic arbors in 3D biomedical image stac ...

We present a novel approach to fully automated reconstruction of tree structures in noisy 2D images. Unlike in earlier approaches, we explicitly handle crossovers and bifurcation points, and impose geometric constraints while optimizing a global cost funct ...

We propose a novel approach to automatically tracking elliptical cell populations in time-lapse image sequences. Given an initial segmentation, we account for partial occlusions and overlaps by generating an over-complete set of competing detection hypothe ...

We propose a novel approach to automated delineation of linear structures that form complex and potentially loopy networks. This is in contrast to earlier approaches that usually assume a tree topology for the networks. At the heart of our method is an Int ...

We propose a novel Bayesian approach to automated delineation of curvilinear structures that form complex and potentially loopy networks. By representing the image data as a graph of potential paths, we first show how to weight these paths using discrimina ...

In this paper we empirically analyze the importance of sparsifying representations for classification purposes. We focus on those obtained by convolving images with linear filters, which can be either hand designed or learned, and perform extensive experim ...

We present a novel algorithm for the simultaneous segmentation and anatomical labeling of the cerebral vasculature. The method first constructs an over-complete graph capturing the vasculature. It then selects and labels the subset of edges that most likel ...

We propose a novel approach to reconstructing curvilinear tree structures evolving over time, such as road networks in 2D aerial images or neural structures in 3D microscopy stacks acquired in vivo. To enforce temporal consistency, we simultaneously proces ...

In this paper, we show that tracking different kinds of interacting objects can be formulated as a network-flow Mixed Integer Program. This is made possible by tracking all objects simultaneously using intertwined flow variables and expressing the fact tha ...

In this paper, we show that tracking different kinds of interacting objects can be formulated as a network-flow Mixed Integer Program. This is made possible by tracking all objects simultaneously and expressing the fact that one object can appear or disapp ...

Engin Türetken

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Automated Reconstruction of Curvilinear Networks from 2D and 3D Imagery

Leveraging Spatial and Photometric Context for Calibrated Non-Lambertian Photometric Stereo

Tubular Geodesics using Oriented Flux: An ITK Implementation

Reconstructing Evolving Tree Structures in Time Lapse Sequences

Automated Reconstruction of Tree Structures using Path Classifiers and Mixed Integer Programming

Delineating Trees in Noisy 2D Images and 3D Image Stacks

Automated Reconstruction of Dendritic and Axonal Trees by Global Optimization with Geometric Priors

Multiscale Centerline Detection

Reconstructing Geometrically Consistent Tree Structures from Noisy Images

Network Flow Integer Programming to Track Elliptical Cells in Time-Lapse Sequences

Reconstructing Loopy Curvilinear Structures Using Integer Programming

Reconstructing Curvilinear Networks using Path Classifiers and Integer Programming

On the Relevance of Sparsity for Image Classification

Simultaneous Segmentation and Anatomical Labeling of the Cerebral Vasculature

Reconstructing Evolving Tree Structures in Time Lapse Sequences by Enforcing Time-Consistency

Tracking Interacting Objects Using Intertwined Flows

Detecting Irregular Curvilinear Structures in Gray Scale and Color Imagery using Multi-Directional Oriented Flux

Tracking Interacting Objects Optimally Using Integer Programming

Hybrid Algorithms for the Minimum-Weight Rooted Arborescence Problem