Recent Trends in Image Processing and Pattern Recognition
6th International Conference, RTIP2R 2023, Derby, UK, December 7–8, 2023, Revised Selected Papers, Part II
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Article
High-resolution brain tractography from X-ray phase-contrast images
X-ray phase contrast tomography (XPCT) can produce high contrast isotropic images of biological samples in only a few minutes thanks to the unique properties of the synchrotron X-ray beam. XPCT of brain tissue...
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Book and Conference Proceedings
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Book and Conference Proceedings
Recent Trends in Image Processing and Pattern Recognition
6th International Conference, RTIP2R 2023, Derby, UK, December 7–8, 2023, Revised Selected Papers, Part I
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Chapter and Conference Paper
Segment- and Arc-Based Vectorizations by Multi-scale/Irregular Tangential Covering
In this paper, we propose an original manner to employ a tangential cover algorithm - minDSS - in order to vectorize noisy digital contours. To do so, we exploit the representation of graphical objects by maxi...
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Article
Ontologies for Liver Diseases Representation: A Systematic Literature Review
Ontology, as a useful knowledge engineering technique, has been widely used for reducing ambiguity and hel** with information sharing. It is considered originally to be clear, comprehensive, and with well-de...
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Chapter and Conference Paper
A Novel Deep Learning Approach for Liver MRI Classification and HCC Detection
This work proposes a deep learning algorithm based on the Convolutional Neural Network (CNN) architecture to detect HepatoCellular Carcinoma (HCC) from liver DCE-MRI (Dynamic Contrast-Enhanced MRI) sequences. ...
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Article
Ontology-Based Approach for Liver Cancer Diagnosis and Treatment
Liver cancer is the third deadliest cancer in the world. It characterizes a malignant tumor that develops through liver cells. The hepatocellular carcinoma (HCC) is one of these tumors. Hepatic primary cancer ...
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Chapter and Conference Paper
An Ontological Model for Analyzing Liver Cancer Medical Reports
The rapid adoption of Electronic Health Record (EHR) systems requires advanced enactment strategies for analyzing medical reports. Indeed, the information presented in these reports is difficult to access and ...
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Chapter and Conference Paper
Automatic Identification and Extraction of Pectoral Muscle in Digital Mammography
Mammography is a worldwide image modality used to diagnose breast cancer and can be used to measure breast density (BD). In clinical routine, radiologist perform image evaluations through BIRADS assessment. Ho...
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Chapter and Conference Paper
New Definition of Quality-Scale Robustness for Image Processing Algorithms, with Generalized Uncertainty Modeling, Applied to Denoising and Segmentation
Robustness is an important concern in machine learning and pattern ...
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Chapter and Conference Paper
U-CatcHCC: An Accurate HCC Detector in Hepatic DCE-MRI Sequences Based on an U-Net Framework
This paper presents a novel framework devoted to the detection of HCC (Hepato-Cellular Carcinoma) within hepatic DCE-MRI (Dynamic Contrast-Enhanced MRI) sequences, by a deep learning approach. In clinical rout...
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Chapter and Conference Paper
Reconstructions of Noisy Digital Contours with Maximal Primitives Based on Multi-scale/Irregular Geometric Representation and Generalized Linear Programming
The reconstruction of noisy digital shapes is a complex question and a lot of contributions have been proposed to address this problem, including blurred segment decomposition or adaptive tangential covering f...
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Chapter and Conference Paper
Greyscale Image Vectorization from Geometric Digital Contour Representations
In the field of digital geometry, numerous advances have been recently made to efficiently represent a simple polygonal shape; from dominant points of a curvature-based representation, a binary shape is effici...
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Chapter and Conference Paper
Medical Image Processing and Numerical Simulation for Digital Hepatic Parenchymal Blood Flow
This paper deals with the personalized simulation of blood flow within the liver parenchyma, by considering a complete pipeline of medical image segmentation, organ volume reconstruction, and numerical simulat...
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Chapter and Conference Paper
A Novel Definition of Robustness for Image Processing Algorithms
As image gains much wider importance in our society, image processing has found various applications since the 60’s: biomedical imagery, security and many more. A highly common issue in those processes is the ...
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Chapter and Conference Paper
Robust Computations of Reeb Graphs in 2-D Binary Images
In this article, we present a novel approach devoted to robustly compute the Reeb graph of a digital binary image, possibly altered by noise. We first employ a skeletonization algorithm, named DECS (Discrete E...
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Chapter and Conference Paper
About the Maximum Cardinality of the Digital Cover of a Curve with a Given Length
We prove that the number of pixels -with pixels as unit lattice squares- of the digitization of a curve Γ of Euclidean length l is less than ...
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Chapter and Conference Paper
A Benchmark Dataset for Outdoor Foreground/Background Extraction
Most of video-surveillance based applications use a foreground extraction algorithm to detect interest objects from videos provided by static cameras. This paper presents a benchmark dataset and evaluation pro...
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Chapter and Conference Paper
Arc Recognition on Irregular Isothetic Grids and Its Application to Reconstruction of Noisy Digital Contours
In the present paper, we introduced an arc recognition technique suitable for irregular isothetic object. It is based on the digital inter-pixel (DIP) circle model, a pixel-based representation of the Kovalevs...
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Chapter
Separable Distance Transformation and Its Applications
In binary shape analysis, the distance transformation (DT) and its by-products are fundamental in many applications since they provide volumetric and metric information about the input shape. In this chapter, ...
