29 papers · ranked by Valyu relevance
Kazeem Oyeyemi Oyebode, Shengzhi Du, Barend Jacobus van Wyk, Karim Djouani
'Karim Djouani'] Graph cut segmentation provides a platform to analyze images through a global segmentation strategy, and as a result of this, it has gained a wider acceptability in many interactive and automatic segmentation fields of application, such as the medical field. The graph cut energy function has a…
Hajar Danesh, Raheleh Kafieh, Hossein Rabbani, Fedra Hajizadeh
The introduction of enhanced depth imaging optical coherence tomography (EDI-OCT) has provided the advantage of in vivo cross-sectional imaging of the choroid, similar to the retina, with standard commercially available spectral domain (SD) OCT machines. A texture-based algorithm is introduced in this paper for fully…
M. Dirnberger, T. Kehl, A. Neumann
Networks are amongst the central building blocks of many systems. Given a graph of a network, methods from graph theory enable a precise investigation of its properties. Software for the analysis of graphs is widely available and has been applied to study various types of networks. In some applications, graph…
Adrian Wolny, Lorenzo Cerrone, Athul Vijayan, Rachele Tofanelli + 13 more
Quantitative analysis of plant and animal morphogenesis requires accurate segmentation of individual cells in volumetric images of growing organs. In the last years, deep learning has provided robust automated algorithms that approach human performance, with applications to bio-image analysis now starting to emerge.…
Yuzhong Chen, Zhenyu Liu, Yulin Liu, Chen Dong
Attack graph modeling aims to generate attack models by investigating attack behaviors recorded in intrusion alerts raised in network security devices. Attack models can help network security administrators discover an attack strategy that intruders use to compromise the network and implement a timely response to…
Jan Egger, Tina Kapur, Thomas Dukatz, Malgorzata Kolodziej + 4 more
'Dženan Zukić' 'Bernd Freisleben' 'Christopher Nimsky' 'Yong Fan'] We present a rectangle-based segmentation algorithm that sets up a graph and performs a graph cut to separate an object from the background. However, graph-based algorithms distribute the graph's nodes uniformly and equidistantly on the image. Then, a…
Wang, Cong, Pedrycz, Witold + 6 more
—G-images refer to image data defined on irregular graph domains. This work elaborates a similarity-preserving Fuzzy C-Means (FCM) algorithm for G-image segmentation and aims to develop techniques and tools for segmenting G-images. To preserve the membership similarity between an arbitrary image pixel and its…
Gene Cheung, Enrico Magli, Yuichi Tanaka, Michael K. Ng
—Recent advent of graph signal processing (GSP) has spurred intensive studies of signals that live naturally on irregular data kernels described by graphs (e.g., social networks, wireless sensor networks). Though a digital image contains pixels that reside on a regularly sampled 2D grid, if one can design an…
Youssef Mourchid, Mohammed El Hassouni, Hocine Cherifi
With the recent advances in complex networks theory, graph-based techniques for image segmentation has attracted great attention recently. In order to segment the image into meaningful connected components, this paper proposes an image segmentation general framework using complex networks based community detection…
Elyas Heidari, Andrew Moorman, Dániel Unyi, Nikhita Pasnuri + 8 more
The accurate assignment of transcripts to their cells of origin remains the Achilles heel of imaging-based spatial transcriptomics, despite being critical for nearly all downstream analyses. Current cell segmentation methods are prone to over- and under-segmentation, misassign transcripts to cells, require manual…
Andrew Hynes, Stephen Czarnuch
We present a method of segmenting human parts in depth images, when provided the image positions of the body parts. The goal is to facilitate per-pixel labelling of large datasets of human images, which are used for training and testing algorithms for pose estimation and automatic segmentation. A common technique in…
Siegfried Dubois, Matthias Zytnicki, Claire Lemaitre, Thomas Faraut
Pangenome variation graphs are an increasingly used tool to perform genome analysis, aiming to replace a linear reference in a wide variety of genomic analyses. The construction of a variation graph from a collection of chromosome-size genome sequences is a difficult task that is generally addressed using a number of…
Jeová Farias Sales Rocha Neto, Pedro F. Felzenszwalb
We introduce a new spectral method for image segmentation that incorporates long range relationships for global appearance modeling. The approach combines two different graphs, one is a sparse graph that captures spatial relationships between nearby pixels and another is a dense graph that captures pairwise similarity…
Tatsuya Haga, Tomoki Fukai
Our cognition relies on the ability of the brain to segment hierarchically structured events on multiple scales. Recent evidence suggests that the brain performs this event segmentation based on the structure of state-transition graphs behind sequential experiences. However, the underlying circuit mechanisms are only…
Oscar Cuadros Linares, Glenda Michele Botelho, Francisco A. Rodrigues, João Batista Soares Neto
'João Batista Soares Neto'] Abstract: Image segmentation has many applications which range from machine learning to medical diagnosis. In this paper, we propose a framework for the segmentation of images based on super-pixels and algorithms for community identification in graphs. The super-pixel presegmentation step…
Liping Yang, Joshua Driscol, Ming Gong, Shujie Wang + 1 more
algorithm for line detection from images Authors: ['Liping Yang' 'Joshua Driscol' 'Ming Gong' 'Shujie Wang' 'Catherine Potts'] - 1 GeoAIR Lab, Department of Geography and Environmental Studies, University of New Mexico, Albuquerque, NM 87131, USA - 2 Center for the Advancement of Spatial Informatics Research and…
Ayelet Heimowitz, Yosi Keller
—This work presents an unsupervised and semiautomatic image segmentation approach where we formulate the segmentation as a inference problem based on unary and pairwise assignment probabilities computed using low-level image cues. The inference is solved via a probabilistic graph matching scheme, which allows rigorous…
Justin A. Eichel, Alexander Wong, Paul Fieguth, David A. Clausi + 1 more
'Jesus Gomez-Gardenes'] Spectral clustering methods have been shown to be effective for image segmentation. Unfortunately, the presence of image noise as well as textural characteristics can have a significant negative effect on the segmentation performance. To accommodate for image noise and textural characteristics…
Yen-Ju Chen, Zitang Sun, Shin’ya Nishida
Perceptual organization in the human visual system involves neural mechanisms that spatially group and segment image areas based on local feature similarities, such as the temporal correlation of luminance changes. Successful segmentation models in computer vision, including graph-based algorithms and vision…
Agata Łabiak, Anees Kazi, Chantal Pellegrini, Aina Frau-Pascual + 1 more
Due to the significant amount of time and expertise needed for manual segmentation of the brain cortex from magnetic resonance imaging (MRI) data, there is a substantial need for efficient and accurate algorithms to replace the need for human involvement. In this work, we explore the capabilities of Graph Neural…
Laurent Najman, Jean Cousty
Mathematical morphology was born almost 50 years ago (Serra, 1982), initialy an evolution of a continuous probabilistic framework (Matheron, 1975). Historically, this was the first consistent non-linear image analysis theory which from the very start included not only theoretical results, but also many practical…
Michael Hutcheon, Andrew Teale
Algorithms are presented for performing a topological analysis of an arbitrary function, evaluated on an arbitrary grid of points. These algorithms work strictly by post-processing the data and require no additional function evaluations. This is achieved by connecting the grid points with a neighbourhood graph…
Lionel Zoubritzky, François-Xavier Coudert
We present here an open-source Julia library for the topological identification of crystalline materials, with algorithmic and computational improvements over the previously available software in the field, resulting in a speed increase of one order of magnitude. This new algorithm and implementation can therefore be…
Authors not listed
Identifying synthesis routes from knowledge graphs poses challenges beyond retrosynthesis, including path–finding artifacts and data issues. We introduce “SynGPS”, a novel algorithm that overcomes these limitations by identifying viable routes even with common artifacts. SynGPS can resolve nonsensical cycles…
Alexander E. Siemenn, Eunice Aissi, Fang Sheng, Armi Tiihonen + 3 more
In materials research, the task of characterizing hundreds of different materials traditionally requires equally many human hours spent measuring samples one by one. We demonstrate that with the integration of computer vision into this material research workflow, many of these tasks can be automated, significantly…
Ping Yang, E. Adrian Henle, Xiaoli Fern, Cory M. Simon
Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are agriculturally and ecologically vital as pollinators. The development of new pesticides---driven by pest resistance to and demands to reduce negative environmental impacts of…
Authors not listed
We present a unified, set–theoretic framework that extends molecular graphs to hypergraphs and superhypergraphs via iterated power sets. We define Molecular Graphs, Molecular HyperGraphs, and Molecular SuperHyperGraphs, and develop four complements over them: Weighted, Rough, Neural, and Multipolar frameworks. We prove…
Authors not listed
SynTemp is a framework designed to extract and hierarchically cluster reaction templates from large-scale reaction data repositories. Reaction templates are partial Imaginary Transition State graphs representing the reaction center as well as surrounding context. These graphs are equivalent to Double Pushout graph…
Authors not listed
A directed graph (or digraph) consists of a finite vertex set 𝑉 and a set of ordered edges 𝐸 ⊆ 𝑉 × 𝑉, each edge (𝑢, 𝑣) indicating a one-way connection from 𝑢 (source) to 𝑣 (target). A bidirected graph is a generalization of an undirected graph where each edge is assigned a direction at each of its endpoints…