Search results for "Detection"
showing 10 items of 2543 documents
Computer Aided Design for Diabetic Retinopathy
2013
International audience; Computer aided diagnosis and follow up can help in prevention and treatment of diabetes and its related complications. This paper presents a summary of the results we obtained over the last few years regarding the development of a CAD system for diabetic retinopathy. We present a methodology for diagnosis of DME based on exudates segmentation, as well as an automated detection of micro-aneurysm (MA) and DR diagnosis; Our approach uses standard available public database and shows a high power of generalization through cross database experiments.
Colorimetric and fluorescent hydrazone-BODIPY probes for the detection of γ-hydroxybutyric acid (GHB) and cathinones
2022
Consumption and abuse of drugs is a general problem, which concerns our entire society. In some cases, drugs are used for recreational purposes; but in others, they are used to commit crimes such as Drug-Facilitated Sexual Assault (DFSA). In other cases, this consumption alters the consumer mood in such a way that risky situations can rise. In any case, detection of drugs in different environment is worthwhile. Here, two new chromogenic and fluorescent probes are reported. Detection of both cathinone derivatives and γ-hydroxybutyric acid (GHB) can be carried out with naked-eye with limits of detection of 0.4 μM and 0.3 μM for GHB and 2.0 μM for ephedrone. Selectivity in the presence of othe…
Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni$^{2+}$ Detection
2023
Boron-based nanocomposites are very promising for a wide range of technological applications, spanning from microelectronics to nanomedicine. A large variety of B-based nanomaterials has been already observed, such as borospherene, B nanotubes and nanoparticles, and boron nitride nanoparticles. However, their fabrication usually involves toxic precursors or leads to very low yields or small boron atom concentration. In this work, we report the synthesis of nanometric B$_{2}$O$_{3}$ nanodisks, a family of nanomaterials with a quasi-2D morphology capable of intense fluorescence in the visible range. Such as boron-based nanomaterial, which we synthesized by pulsed laser ablation of a boron tar…
Learning-based multiresolution transforms with application to image compression
2013
In Harten's framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact and predicted values. In this paper we use tools of statistical learning in order to design a more accurate prediction operator in this framework based on a training sample, resulting in multiresolution decompositions with enhanced sparsity. In the case of images, we incorporate edge detection techniques in the design of the prediction operator in order to avoid Gibbs phenomenon. Numerical tests are presented showing that the …
Repeatability Study on a Classifier for Gastric Cancer Detection from Breath Sensor Data
2019
The SNIFFPHONE device is a portable multichannel gas sensor, aiming to detect gastric cancer (GC) from breath samples. It employs gold nanoparticle (GNP) sensors reacting to volatile organic compounds (VOCs) in the exhaled breath, a non-invasive technique to support early diagnosis. This study evaluates the repeatability of the SNIFFPHONE classification result for measurements conducted on healthy subjects over a short period of time of less than 10 minutes. Due to the portable nature of the device, repeatability is studied with respect to varying measurement location. We find the classification results repeatable with a statistically significant 81 % Pearson correlation coefficient, even t…
Lateral flow assays towards point-of-care cancer detection: A review of current progress and future trends
2020
Abstract Cancer is one of the main causes of mortality and morbidity worldwide. However, its early non-invasive detection via quantification of appropriate biomarkers can significantly reduce mortality, enhance survival, and save treatment costs. Lateral flow test strips (LFTS) are nowadays considered as the most attractive point-of-care devices for healthcare applications. However, the quantification of cancer biomarkers in body fluids suffers from some challenges including i) the necessity for multiplex analysis, ii) the development of sensitive detection systems, iii) to overcome the analysis of complex samples, at the same time, it should keep the quality assurance criteria for an accur…
Anomaly‐based intrusion detection systems: The requirements, methods, measurements, and datasets
2021
International audience; With the Internet's unprecedented growth and nations' reliance on computer networks, new cyber‐attacks are created every day as means for achieving financial gain, imposing political agendas, and developing cyberwarfare arsenals. Network security is thus acquiring increasing attention among researchers, practitioners, network architects, policy makers, and others. To defend organizations' networks from existing, foreseen, and future threats, intrusion detection systems (IDSs) are becoming a must. Existing surveys on anomaly‐based IDS (AIDS) focus on specific components such as detection mechanisms and lack many others. In contrast to existing surveys, this article co…
Detection of Duplicated Regions in Tampered Digital Images by Bit-Plane Analysis
2009
In this paper we present a new method for searching duplicated areas in a digital image. The goal is to detect if an image has been tampered by a copy-move process. Our method works within a convenient domain. The image to be analyzed is decomposed in its bit-plane representation. Then, for each bitplane, block of bits are encoded with an ASCII code, and a sequence of strings is analyzed rather than the original bit-plane. The sequence is lexicographically sorted and similar groups of bits are extracted as candidate areas, and passed to the following plane to be processed. Output of the last planes indicates if, and where, the image has been altered.
Automatic multi-seed detection for MR breast image segmentation
2017
In this paper an automatic multi-seed detection method for magnetic resonance (MR) breast image segmentation is presented. The proposed method consists of three steps: (1) pre-processing step to locate three regions of interest (axillary and sternal regions); (2) processing step to detect maximum concavity points for each region of interest; (3) breast image segmentation step. Traditional manual segmentation methods require radiological expertise and they usually are very tiring and time-consuming. The approach is fast because the multi-seed detection is based on geometric properties of the ROI. When the maximum concavity points of the breast regions have been detected, region growing and m…
Convolutional Long Short-Term Memory Network for Multitemporal Cloud Detection Over Landmarks
2019
In this work, we propose to exploit both the temporal and spatial correlations in Earth observation satellite images through deep learning methods. In particular, the combination of a U-Net convolutional neural network together with a convolutional long short-term memory (LSTM) layer is proposed. This model is applied for cloud detection on MSG/SEVIRI image time series over selected landmarks. Implementation details are provided and our proposal is compared against a standard SVM and a U-Net without the convolutional LSTM layer but including temporal information too. Experimental results show that this combination of networks exploits both the spatial and temporal dependence and provides st…