Publications related to Simultaneous Segmentation and Anatomical Labeling of the Cerebral Vasculature

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

Nature Portfolio2024

Confidence Matters: Applications to Semantic Segmentation

Prabhu Teja Sivaprasad

The successes of deep learning for semantic segmentation can in be, in part, attributed to its scale: a notion that encapsulates the largeness of these computational architectures and the labeled datasets they are trained on. These resource requirements hi ...

EPFL2023

Object Priors for Volumetric Image Segmentation

Pamuditha Udaranga Wickramasinghe

Large training datasets have played a vital role in the success of modern deep learning methods in computer vision. But, obtaining sufficient amount of training data is challenging, specially when annotating volumetric images. This is because fully annotat ...

EPFL2022

Improving the Training of Compact Neural Networks for Visual Recognition

Shuxuan Guo

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

EPFL2022

Data reduction for mixed integer linear programming in complex energy systems

Luc Girardin, François Maréchal, Luise Middelhauve, Natalija Ljubic, Julia Granacher

The task of optimally designing and scheduling energy systems with a high share of renewable energies is complex and computationally demanding. A widespread method for tackling this task is to apply mixed integer linear programming (MILP). Even though the ...

2021

A Novel Decomposition Solution Approach for the Restoration Problem in Distribution Networks

Sidi-Rachid Cherkaoui, Hossein Sekhavatmanesh

The distribution network restoration problem is by nature a mixed integer and non-linear optimization problem due to the switching decisions and Optimal Power Flow (OPF) constraints, respectively. The link between these two parts involves logical implicati ...

IEEE Institute of Electrical and Electronics Engineers2020

Proximity Results and Faster Algorithms for Integer Programming Using the Steinitz Lemma

Friedrich Eisenbrand

We consider integer programming problems in standard form max{c(T)x : Ax = b, x >= 0, x is an element of Z(n)} where A is an element of Z(mxn), b is an element of Z(m), and c is an element of Z(n). We show that such an integer program can be solved in time ...

ASSOC COMPUTING MACHINERY2020

TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation

Pascal Fua, Leonardo Citraro, Mateusz Kozinski, Subeesh Vasu

Most state-of-the-art approaches to road extraction from aerial images rely on a CNN trained to label road pixels as foreground and remainder of the image as background. The CNN is usually trained by minimizing pixel-wise losses, which is less than ideal t ...

2020

An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy

Georges Wagnières, Sharib Ali, Xiaokang Wang

We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art computer vis ...

Nature Research2020

New Results in Integer and Lattice Programming

Christoph Hunkenschröder

An integer program (IP) is a problem of the form

\min \{f(x) : \, Ax = b, \ l \leq x \leq u, \ x \in \Z^n\}

, where

A \in \Z^{m \times n}

,

b \in \Z^m

,

l,u \in \Z^n

, and

f: \Z^n \rightarrow \Z

is a separable convex objective function. The problem o ...

EPFL2020

The electric autonomous dial-a-ride problem

Claudia Bongiovanni

This thesis develops mathematical programming frameworks to operate electric autonomous vehicles in the context of ride-sharing services. The introduced problem is a novel variant of the Dial-a-Ride Problem (DARP), denoted by the electric Autonomous Dial-a ...

EPFL2020

Learning to Reduce Annotation Load

Ksenia Konyushkova

Modern machine learning methods and their applications in computer vision are known to crave for large amounts of training data to reach their full potential. Because training data is mostly obtained through humans who manually label samples, it induces a ...

EPFL2019

Geometry in active learning for binary and multi-class image segmentation

Pascal Fua, Raphael Sznitman, Ksenia Konyushkova

We propose an active learning approach to image segmentation that exploits geometric priors to speed up and streamline the annotation process. It can be applied for both background foreground and multi-class segmentation tasks in 2D images and 3D image vol ...

2019

Automatic Segmentation of Nuclei in Histopathology Images using Encoding-Decoding Convolutional Neural Networks

Pascal Frossard, Beril Besbinar, Deniz Mercadier

Accurate and fast segmentation of nuclei in histopathological images plays a crucial role in cancer research for detection and grading, as well as personal treatment. Despite the important efforts, current algorithms are still suboptimal in terms of speed, ...

IEEE2019

Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI

Tobias Kober

We proposed a method for segmentation of brain tissues-gray matter, white matter, and cerebrospinal fluid-using multi-contrast images, including a T1 map and a uniform T1-weighted image, from a magnetization-prepared 2 rapid acquisition gradient echoes (MP ...

2019

Probabilistic Atlases to Enforce Topological Constraints

Pascal Fua, Graham Knott, Pamuditha Udaranga Wickramasinghe

Probabilistic atlases (PAs) have long been used in standard segmentation approaches and, more recently, in conjunction with Convolutional Neural Networks (CNNs). However, their use has been restricted to relatively standardized structures such as the brain ...

2019

SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

Anaïs Laure Marie-Thérèse Badoual

Ongoing advances in imaging techniques create new demands regarding the analysis of images in medicine and biology. Image segmentation is a key step of many image analysis pipelines and its proper execution is a particularly challenging task. This thesis i ...

EPFL2019

Color Image Segmentation Using a Fuzzy Inference System

Matin Macktoobian

A novel method is proposed in the scope of image segmentation that solves this problem by breaking it into two main blocks. The first block's functionality is a method to anticipate the color basis of each segment in segmented images. One of the challenges ...

IEEE2019

Learning Approach to Delineation of Curvilinear Structures in 2D and 3D Images

Agata Justyna Mosinska

Detection of curvilinear structures has long been of interest due to its wide range of applications. Large amounts of imaging data could be readily used in many fields, but it is practically not possible to analyze them manually. Hence, the need for automa ...

EPFL2019

Enhanced MR Image Classification Using Hybrid Statistical and Wavelets Features

Mohammad Khaja Nazeeruddin

Classification of brain tumor is one of the most vital tasks within medical image processing. Classification of images greatly depends on the features extracted from the image, and thus, feature extraction plays a great role in the correct classification o ...

2019