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A computer-aided diagnosis system for HEp-2 fluorescence intensity classification
摘要： Background and objective: The indirect immunofluorescence (IIF) on HEp-2 cells is the recommended technique for the detection of antinuclear antibodies. However, it is burdened by some limitations, as it is time consuming and subjective, and it requires trained personnel. In other fields the adoption of deep neural networks has provided an effective high-level abstraction of the raw data, resulting in the ability to automatically generate optimized high-level features. Methods: To alleviate IIF limitations, this paper presents a computer-aided diagnosis (CAD) system classifying HEp-2 fluorescence intensity: it represents each image using an Invariant Scattering Convolutional Network (Scatnet), which is locally translation invariant and stable to deformations, a characteristic useful in case of HEp-2 samples. To cope with the inter-observer discrepancies found in the dataset, we also introduce a method for gold standard computation that assigns a label and a reliability score to each HEp-2 sample on the basis of annotations provided by expert physicians. Features by Scatnet and gold standard information are then used to train a Support Vector Machine. Results: The proposed CAD is tested on a new dataset of 1771 images annotated by three independent medical centers. The performances achieved by our CAD in recognizing positive, weak positive and negative samples are also compared against those obtained by other two approaches presented so far in the literature. The same system trained on this new dataset is then tested on two public datasets, namely MIVIA and I3Asel. Conclusions: The results confirm the effectiveness of our proposal, also revealing that it achieves the same performance as medical experts.
关键词： HEp-2 samples,Deep learning,Invariant Scattering Convolutional Networks,Computer-aided diagnosis,Indirect immunofluorescence
更新于2025-09-23 15:21:21
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Improving clinical diagnosis of early-stage cutaneous melanoma based on Raman spectroscopy
摘要： BACKGROUND: Clinical diagnosis of early melanoma (Breslow thickness less than 0.8 mm) is crucial to disease-free survival. However, it is subjective and can be exceedingly difficult, leading to missed melanomas, or unnecessary excision of benign pigmented skin lesions. An objective technique is needed to improve the diagnosis of early melanoma. METHODS: We have developed a method to improve diagnosis of (thin) melanoma, based on Raman spectroscopy. In an ex vivo study in a tertiary referral (pigmented lesions) centre, high-wavenumber Raman spectra were collected from 174 freshly excised melanocytic lesions suspicious for melanoma. Measurements were performed on multiple locations within the lesions. A diagnostic model was developed and validated on an independent data set of 96 lesions. RESULTS: Approximately 60% of the melanomas included in this study were melanomas in situ. The invasive melanomas had an average Breslow thickness of 0.89 mm. The diagnostic model correctly classified all melanomas (including in situ) with a specificity of 43.8%, and showed a potential improvement of the number needed to treat from 6.0 to 2.7, at a sensitivity of 100%. CONCLUSION: This work signifies an important step towards accurate and objective clinical diagnosis of melanoma and in particular melanoma with Breslow thickness <0.8 mm.
关键词： dermatology,Raman spectroscopy,early diagnosis,Breslow thickness,melanoma
更新于2025-09-23 15:21:21
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Si, N-codoped carbon dots: preparation and application in iron overload diagnosis
摘要： Heteroatom doping is a straightforward and smart strategy to improve the fluorescence efficiency of carbon dots (CDs). We synthesized the Si, N-codoped CDs (SiNCDs) with high quantum yield up to 29.7% through one-step hydrothermal method. The linear range for Fe3+ was between 0 and 200 μM, and the limit of detection was about 5 μM, which presented potential for Fe quantification in serum to diagnose Fe overload. In addition, the SiNCDs demonstrated good selectivity to Fe3+ among high concentrations of metal ions, amino acids and H2O2, so there is no need to mix additional reagents as the colorimetric method does in clinic, making SiNCDs more competitive in clinical application. Furthermore, we explored the practicability of SiNCDs by detecting Fe in serum from five healthy volunteers and three patients suffering Fe overload. The recovery rate was from 87.1 to 113.6%, which confirmed the application prospect of SiNCDs in clinical diagnostics.
关键词： N-codoped carbon dots,hydrothermal method,Si,iron overload diagnosis,fluorescence efficiency,quantum yield
更新于2025-09-23 15:21:21
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[IEEE 2019 24th Microoptics Conference (MOC) - Toyama, Japan (2019.11.17-2019.11.20)] 2019 24th Microoptics Conference (MOC) - Patterned emission of organic light emitting diodes with laser irradiation
摘要： Self-healing networks aim to detect cells with service degradation, identify the fault cause of their problem, and execute compensation and repair actions. The development of this type of automatic system presents several challenges to be confronted. The first challenge is the scarce number of historically reported faults, which greatly complicates the evaluation of novel self-healing techniques. For this reason, in this paper, a system model to simulate faults in Long-Term Evolution (LTE) networks, along with their most significant key performance indicators, is proposed. Second, the expert knowledge required to build a self-healing system is usually not documented. Therefore, in this paper, a methodology to extract this information from a collection of reported cases is proposed. Finally, following the proposed methodology, an automatic fuzzy-logic-based system for fault identification in LTE networks is designed. Evaluation results show that the fuzzy system provides fault identification with a high success rate.
关键词： Long-Term Evolution (LTE),Diagnosis,fuzzy logic,fault identification,troubleshooting,root cause analysis,self-healing,fault management
更新于2025-09-23 15:21:01
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Optical Diagnosis of the Geometry of an Axisymmetric Controlled Nozzle of a Gas-Turbine Engine
摘要： Modern aviation industry solves the problem of developing multifunction engines capable of ?ying both at subsonic and supersonic speeds. An important part in such engines is a variable area nozzle, which allows varying the geometry of the engine exhaust unit and, accordingly, its technical characteristics. This study touches upon an computer vision based optical noncontact method for reconstructing a nozzle shape. The reconstruction requires data recorded by two optical three-dimensional recorders directed toward the inner part of the nozzle when the engine is subjected to ground tests. The diagnosis is complicated by the presence of a hot jet being in the way of the sensor vision, the regime-dependent variation of the nozzle glow brightness, and intense mechanical vibrations. The performed bench tests con?rm the e?ciency of the proposed method. According to their results, in a low-gas regime, the standard deviation of the diagnosed diameters of the exhaust unit and critical sections for each frame does not exceed 0.3% of the corresponding sizes. The data obtained as a result of this diagnosis can be taken into account when upgrading the exhaust unit of the engine and the thrust control system of a gas turbine engine.
关键词： 3D scan,GTE exhaust unit geometry,optical diagnosis,stereo vision,stereo reconstruction,ground tests
更新于2025-09-23 15:21:01
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[IEEE 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - Rome, Italy (2019.6.17-2019.6.20)] 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - System Level Analysis of Millimetre-wave GaN-based MIMO Radar for Detection of Micro Unmanned Aerial Vehicles
摘要： A particle filter (PF)-based robust navigation with fault diagnosis (FD) is designed for an underwater robot, where 10 failure modes of sensors and thrusters are considered. The nominal underwater robot and its anomaly are described by a switching-mode hidden Markov model. By extensively running a PF on the model, the FD and robust navigation are achieved. Closed-loop full-scale experimental results show that the proposed method is robust, can diagnose faults effectively, and can provide good state estimation even in cases where multiple faults occur. Comparing with other methods, the proposed method can diagnose all faults within a single structure, diagnose simultaneous faults, and it is easily implemented.
关键词： fault tolerance,Fault diagnosis (FD),switch-mode hidden Markov model (HMM),particle filter (PF),remotely operated underwater vehicle (ROV),underwater navigation
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin) - Berlin, Germany (2019.9.8-2019.9.11)] 2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin) - Case Study of Photovoltaic Energy Surplus Absorption by Charging Lithium-Ion Batteries Considering Chargea??Discharge Energy Efficiency
摘要： In Autumn 2018, reductive control of photovoltaic surplus energy was performed in Kyushu, Japan. This was a lost opportunity to utilize renewable energy, which could have been otherwise stored in rechargeable batteries. In this study, we simulated the absorption of the photovoltaic energy surplus by charging battery systems of a working electric vehicle considering the energy efficiency of lithium-ion battery systems to reduce the operation cost. This study clarified the quantitative effects of a real-time energy efficiency diagnosis of lithium-ion battery systems. From the simulation results, we discovered that the improvements of the charge–discharge energy loss and the economic gain of the photovoltaic energy surplus absorption depended on the input–output power of the bidirectional vehicle- to-grid charger and the amount of surplus energy. When the input–output power is sufficiently high and the ratio of surplus energy to total capacity of the battery systems is sufficiently low, is the reasonable. The real-time degradation diagnosis of the battery systems and selection considering charge–discharge energy efficiency is necessary to improve the profit from surplus energy absorption.
关键词： charge – discharge energy efficiency,Lithium-ion battery,degradation diagnosis,photovoltaic surplus energy,working electric vehicle
更新于2025-09-23 15:21:01
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Diagnosis and prognosis of myocardial infarction on a plasmonic chip
摘要： Cardiovascular diseases lead to 31.5% of deaths globally, and particularly myocardial infarction (MI) results in 7.4 million deaths per year. Diagnosis of MI and monitoring for prognostic use are critical for clinical management and biomedical research, which require advanced tools with accuracy and speed. Herein, we developed a plasmonic gold nano-island (pGold) chip assay for diagnosis and monitoring of MI. On-chip microarray analysis of serum biomarkers (e.g., cardiac troponin I) afforded up to 130-fold enhancement of near-infrared fluorescence for ultra-sensitive and quantitative detection within controlled periods, using 10 μL of serum only. The pGold chip assay achieved MI diagnostic sensitivity of 100% and specificity of 95.54%, superior to the standard chemiluminescence immunoassay in cardiovascular clinics. Further, we monitored biomarker concentrations regarding percutaneous coronary intervention for prognostic purpose. Our work demonstrated a designed approach using plasmonic materials for enhanced diagnosis and monitoring for prognostic use towards point-of-care testing.
关键词： myocardial infarction,plasmonic gold nano-island chip,diagnosis,monitoring,point-of-care testing
更新于2025-09-23 15:21:01
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Failure Diagnosis Method of Photovoltaic Generator Using Support Vector Machine
摘要： The capacity of photovoltaic (PV) generators can increase owing to the 4030 policy of the Government of South Korea.. In addition, there has been significant interest in developing a technology for the maintenance of PV generators owing to an increase in the number of outdated PV generators. This paper describes a failure diagnosis method that uses operational data for power generation and solar radiation of PV generators. The measured data stored since four years in an operational 50-kW PV generator that was installed in 2014, were analyzed. The proposed failure diagnosis logic uses support vector machine classification as a failure diagnosis method that can classify normal and failure data. The failure data were processed to be used as the fault diagnosis logic for solar power generators. A new 50-kW PV generator, which contained no fault data, was used for a case study in this paper. Fault data were generated and the operation data of the PV generators were diagnosed by applying the proposed method. In addition, the accuracy was calculated and the results were analyzed.
关键词： Support vector machine (SVM),Photovoltaic (PV) generator,Failure diagnosis,Fault data
更新于2025-09-23 15:21:01
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[Lecture Notes in Computer Science] Pattern Recognition and Computer Vision Volume 11256 (First Chinese Conference, PRCV 2018, Guangzhou, China, November 23-26, 2018, Proceedings, Part I) || Automatic Measurement of Cup-to-Disc Ratio for Retinal Images
摘要： Glaucoma is a chronic eye disease which results in irreversible vision loss, and the optic cup-to-disc ratio (CDR) is an essential clinical indicator in diagnosing glaucoma, which means precise optic disc (OD) and optic cup (OC) segmentation become an important task. In this paper, we propose an automatic CDR measurement method. The method includes three stages: OD localization and ROI extraction, simultaneous segmentation of OD and OC, and CDR calculation. In the ?rst stage, the morphological operation and the sliding window are combined to ?nd the OD location and extract the ROI region. In the second stage, an improved deep neural network, named U-Net+CP+FL, which consists of U-shape convolutional architecture, a novel concatenating path and a multi-label fusion loss function, is adopted to simultaneously segment the OD and OC. Based on the segmentation results, the CDR value can be calculated in the last stage. Experimental results on the retinal images from public databases demonstrate that the proposed method can achieve comparable performance with ophthalmologist and superior performance when compared with other existing methods. Thus, our method can be a suitable tool for automated glaucoma analysis.
关键词： OD&OC segmentation,Glaucoma diagnosis,Deep neural network,OD localization,Cup-to-disc ratio (CDR)
更新于2025-09-23 15:21:01