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Learning sperm cells part segmentation with class-specific data augmentation
Marcin Jankowski;Emila Lewandowska;Hugues Talbot;Daniel Wesierski;Anna Jezierska
2024 16th International Conference on Human System Interaction (HSI)
Year: 2024 | Conference Paper |
Infertility affects around 15% of couples worldwide. Male fertility problems include poor sperm quality and low sperm count. The advanced fertility treatment methods like ICSI are nowadays supported by vision systems to assist embryologists in selecting good quality sperm. Computer-Assisted Semen Analysis (CASA) provides quantitative and qualitative sperm analysis concerning concentration, motilit...Show More
Binary Morphological Neural Network
2022 IEEE International Conference on Image Processing (ICIP)
Year: 2022 | Conference Paper |
Cited by: Papers (5)
In the last ten years, Convolutional Neural Networks (CNNs) have formed the basis of deep-learning architectures for most computer vision tasks. However, they are not necessarily optimal. For example, mathematical morphology is known to be better suited to deal with binary images. In this work, we create a morphological neural network that handles binary inputs and outputs. We propose their constr...Show More
Incrementally Semi-Supervised Classification of Arthritis Inflammation on a Clinical Dataset
Theodore Aouad;Clementina Lopez-Medina;Charlotte Martin-Peltier;Adrien Bordner;Sisi Yang;Anna Molto;Maxime Dougados;Antoine Feydy;Hugues Talbot
2022 IEEE International Conference on Image Processing (ICIP)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
For best medical imaging application results, learning-based approaches such as deep learning necessitate specific, extensive and precise annotations. Outside well-curated public benchmarks, these are rarely available in practice, and so it becomes necessary to use less-than-perfect annotations. One way of compensating for this is the embedding of anatomical knowledge. Complementing this, there is...Show More
Coronary Artery Centerline Tracking with the Morphological Skeleton Loss
Mario Viti;Hugues Talbot;Bassam Abdallah;Etienne Perot;Nicolas Gogin
2022 IEEE International Conference on Image Processing (ICIP)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Coronary computed tomography angiography (CCTA) provides a non-invasive imaging solution that reliably depicts the anatomy of coronary arteries. Diagnosing coronary artery diseases (CAD) entails a clinical evaluation of stenosis and plaques, which is in turn essential for obtaining a reliable coronary-artery centerline from CCTA 3D imaging. This work proposes a centerline extraction algorithm by c...Show More
Transformer Graph Network for Coronary Plaque Localization in CCTA
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Coronary CT angiography (CCTA) is the only non-invasive imaging technique that reliably depicts the anatomic extent of Coronary Artery Disease (CAD). While occlusion remains a highly predictive indicator of major cardiovascular events (MACE), there is growing evidence that the presence and characteristics of coronary atherosclerosis provide additional prognostic information. In CCTA calcified plaq...Show More
Object Detection With Component-Graphs in Multi-Band Images: Application to Source Detection in Astronomical Images
Thanh Xuan Nguyen;Giovanni Chierchia;Oleksandra Razim;Reynier F. Peletier;Laurent Najman;Hugues Talbot;Benjamin Perret
In the context of mathematical morphology, component-graphs are complex but powerful structures for multi-band image modeling, processing, and analysis. In this work, we propose a novel multi-band object detection method relying on the component-graphs and statistical hypothesis tests. Our analysis shows that component-graphs are better at capturing image structures compared to the classical compo...Show More
Does Super-Resolution Improve OCR Performance In The Real World? A Case Study On Images Of Receipts
2020 IEEE International Conference on Image Processing (ICIP)
Year: 2020 | Conference Paper |
Cited by: Papers (2)
Recently, many deep learning methods have been used to handle single image super-resolution (SISR) tasks and often achieve state-of-the-art performance. From a visual point of view, the results look convincing. Yet, does it mean that those techniques are reliable and robust enough to be implemented in real business cases to enhance the performance of other computer vision tasks? In this article, w...Show More
CGO: Multiband Astronomical Source Detection With Component-Graphs
Thanh Xuan Nguyen;Giovanni Chierchia;Laurent Najman;Aku Venhola;Caroline Haigh;Reynier Peletier;Michael H.F. Wilkinson;Hugues Talbot;Benjamin Perret
2020 IEEE International Conference on Image Processing (ICIP)
Year: 2020 | Conference Paper |
Cited by: Papers (3)
Component-graphs provide powerful and complex structures for multi-band image processing. We propose a multiband astronomical source detection framework with the component-graphs relying on a new set of component attributes. We propose two modules to differentiate nodes belong to distinct objects and to detect partial object nodes. Experiments demonstrate an improved capacity at detecting faint ob...Show More
A High Performance of Single Cell Imaging Detection with Deep Learning
S. B. Luo;K. T. Nguyen;X. D. Jiang;J. F. Wu;B. H. Wen;Y. Zhang;G. Chierchia;H. Talbot;T. Bourouina;D. L. Kwong;A. Q. Liu
2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC)
Year: 2019 | Conference Paper |
Cited by: Patents (1)
Single cell imaging enables new applications such as biomedical diagnostics, food inspection, and water quality monitoring. In this paper, we study the cell imaging-based machine learning techniques for high-performance cell detection. By taking the advantage of deep learning and imaging flow cytometry, we manage to detect Cryptosporidium and Giardia cells in the bright-field images with high accu...Show More
$n$ D Variational Restoration of Curvilinear Structures With Prior-Based Directional Regularization
Odyssée Merveille;Benoît Naegel;Hugues Talbot;Nicolas Passat
Curvilinear structure restoration in image processing procedures is a difficult task, which can be compounded when these structures are thin, i.e., when their smallest dimension is close to the resolution of the sensor. Many recent restoration methods involve considering a local gradient-based regularization term as prior, assuming gradient sparsity. An isotropic gradient operator is typically not...Show More
Generation of Patient-Specific Cardiac Vascular Networks: A Hybrid Image-Based and Synthetic Geometric Model
Clara Jaquet;Laurent Najman;Hugues Talbot;Leo Grady;Michiel Schaap;Buzzy Spain;Hyun Jin Kim;Irene Vignon-Clementel;Charles A. Taylor
Objective: In this paper, we propose an algorithm for the generation of a patient-specific cardiac vascular network starting from segmented epicardial vessels down to the arterioles. Method: We extend a tree generation method based on satisfaction of functional principles, named constrained constructive optimization, to account for multiple, competing vascular trees. The algorithm simulates angiog...Show More
A Multicore Convex Optimization Algorithm with Applications to Video Restoration
Feriel Abbouds;Emilie Chouzenoux;Jean-Christophe Pesquet;Hugues Talbot
2018 25th IEEE International Conference on Image Processing (ICIP)
Year: 2018 | Conference Paper |
In this paper, we present a new distributed algorithm for minimizing a sum of non-necessarily differentiable convex functions composed with arbitrary linear operators. The overall cost function is assumed strongly convex. Each involved function is associated with a node of a hypergraph having the ability to communicate with neighboring nodes sharing the same hyperedge. Our algorithm relies on a pr...Show More
Spatially variant PSF modeling in confocal macroscopy
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
Year: 2018 | Conference Paper |
Cited by: Papers (3)
The point spread function (PSF) of imaging systems plays an essential role in image reconstruction. In the context of confocal microscopy, optical performance degrades towards the edge of the field of view. In confocal macroscopy, the related artifacts are even stronger, as the field of view is much larger. Because the related PSFs are strongly spatially variant, it is essential to be able to mode...Show More
Curvilinear Structure Analysis by Ranking the Orientation Responses of Path Operators
Odyssée Merveille;Hugues Talbot;Laurent Najman;Nicolas Passat
The analysis of thin curvilinear objects in 3D images is a complex and challenging task. In this article, we introduce a new, non-linear operator, called RORPO (Ranking the Orientation Responses of Path Operators). Inspired by the multidirectional paradigm currently used in linear filtering for thin structure analysis, RORPO is built upon the notion of path operator from mathematical morphology. T...Show More
Flicker removal and superpixel-based motion tracking for high speed videos
2017 IEEE International Conference on Image Processing (ICIP)
Year: 2017 | Conference Paper |
Cited by: Papers (7)
Flicker removal consists of filtering out rapid, artefactual changes of luminosity and colorimetry from image sequences in order to improve colorimetry consistency between video frames. It is a necessary and fundamental task in multiple applications, for instance in archived film sequences, image/video compression and time-lapse videos. In recent years, the wider availability of fast video acquisi...Show More
Periodic area-of-motion characterization for bio-medical applications
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
Year: 2017 | Conference Paper |
Many bio-medical applications involve the analysis of sequences for motion characterization. In this article, we consider 2D+t sequences where a particular motion (e.g. a blood flow) is associated with a specific area of the 2D image (e.g. an artery) but multiple motions may exist simultaneously in the same sequences (e.g. there may be several blood vessels present, each with their specific flow)....Show More
Classification of the dermal-epidermal junction using in-vivo confocal microscopy
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
Year: 2017 | Conference Paper |
Cited by: Papers (4)
Reflectance confocal microscopy (RCM) is a powerful tool to visualize the skin layers at cellular resolution. The dermal-epidermal junction (DEJ) is a thin complex 3D structure. It appears as a low-contrasted structure in confocal en-face sections, which is difficult to recognize visually, leading to uncertainty in the classification. In this article, we propose an automated method for segmenting ...Show More
Automated 3D lymphoma lesion segmentation from PET/CT characteristics
Éloïse Grossiord;Hugues Talbot;Nicolas Passat;Michel Meignan;Laurent Najman
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
Year: 2017 | Conference Paper |
Cited by: Papers (21)
Positron Emission Tomography (PET) using 18F-FDG is recognized as the modality of choice for lymphoma, due to its high sensitivity and specificity. Its wider use for the detection of lesions, quantification of their metabolic activity and evaluation of response to treatment demands the development of accurate and reproducible quantitative image interpretation tools. An accurate tumour delineation ...Show More
Morphological PDEs on graphs for analyzing unorganized data in 3D and higher
2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
Year: 2016 | Conference Paper |
Mathematical morphology operators can be defined in terms of algebraic (discrete) sets or as partial differential equations (PDEs). In our previous works [1, 2], we have proposed a simple method to solve PDEs (Partial Differential Equations) on dataset using the framework PdEs (Partial difference Equations) on graphs. In this paper, we propose to apply morphological-based operators on unorganized ...Show More
Image restoration and segmentation using the Ambrosio-Tortorelli functional and Discrete Calculus
2016 23rd International Conference on Pattern Recognition (ICPR)
Year: 2016 | Conference Paper |
Cited by: Papers (8)
Essential image processing and analysis tasks, such as image segmentation, simplification and denoising, can be conducted in a unified way by minimizing the Mumford-Shah (MS) functional. Although seductive, this minimization is in practice difficult because it requires to jointly define a sharp set of contours and a smooth version of the initial image. For this reason, various relaxations of the o...Show More
Automating the measurement of physiological parameters: A case study in the image analysis of cilia motion
E. Puybareau;H. Talbot;E. Bequignon;B. Louis;G. Pelle;J.-F. Papon;A. Coste;L. Najman
2016 IEEE International Conference on Image Processing (ICIP)
Year: 2016 | Conference Paper |
Cited by: Papers (3)
As image processing and analysis techniques improve, an increasing number of procedures in bio-medical analyses can be automated. This brings many benefits, e.g improved speed and accuracy, leading to more reliable diagnoses and follow-up, ultimately improving patients outcome. Many automated procedures in bio-medical imaging are well established and typically consist of detecting and counting var...Show More
A variational model for thin structure segmentation based on a directional regularization
Odyssée Merveille;Olivia Miraucourt;Stéphanie Salmon;Nicolas Passat;Hugues Talbot
2016 IEEE International Conference on Image Processing (ICIP)
Year: 2016 | Conference Paper |
Cited by: Papers (8)
Tubular structure segmentation is an important task, with many applications in medical image analysis such as vessel segmentation both in 2D and 3D. However, this task is challenging due to the spatial sparsity of these objects, implying a high sensitivity to noise. An important cue in this context is the local orientation of the tubular structures. Using this information, it is possible to regula...Show More
Automated quantification of the epidermal aging process using in-vivo confocal microscopy
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)
Year: 2016 | Conference Paper |
Cited by: Papers (4)
Reflectance confocal microscopy (RCM) is a powerful tool to visualize the skin layers at cellular resolution. The epidermal layer appears as a honeycomb pattern, whose regularity decreases with age. Our aim is to provide a method to automatically quantify the regularity of the honeycomb pattern. The proposed strategy relies on a cell-level supervised classification as regular or irregular using sp...Show More
Automated heart rate estimation in fish embryo
2015 International Conference on Image Processing Theory, Tools and Applications (IPTA)
Year: 2015 | Conference Paper |
Cited by: Papers (6)
Transparent organisms such as fish embryos are being increasingly used for environmental toxicology studies. These studies require estimating a number of physiological parameters. These estimations may be diverse in nature and can be a challenge to automate. Among these, an example is the development of reliable and repeatable automated assays for the determination of heart rates. To achieve this,...Show More
Multicriteria 3D PET image segmentation
Francisco Javier Alvarez Padilla;Éloïse Grossiord;Barbara Romaniuk;Benoît Naegel;Camille Kurtz;Hugues Talbot;Laurent Najman;Romain Guillemot;Dimitri Papathanassiou;Nicolas Passat
2015 International Conference on Image Processing Theory, Tools and Applications (IPTA)
Year: 2015 | Conference Paper |
Cited by: Papers (5)
The analysis of images acquired with Positron Emission Tomography (PET) is challenging. In particular, there is no consensus on the best criterion to quantify the metabolic activity for lesion detection and segmentation purposes. Based on this consideration, we propose a versatile knowledge-based segmentation methodology for 3D PET imaging. In contrast to previous methods, an arbitrary number of q...Show More
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