当前位置： SCI文献检索 > IEEE Journal of Biomedical and Health Informatics期刊下所有文献 > Tear Film Classification in Interferometry Eye Images Using Phylogenetic Diversity Indexes and Ripley's K Function.

Tear Film Classification in Interferometry Eye Images Using Phylogenetic Diversity Indexes and Ripley's K Function.

Abstract：

:Dry eye syndrome is one of the most frequently reported eye diseases in ophthalmological practice. The diagnosis of this disease is a challenging task due to its multifactorial etiology. One of the most applied tests is the manual classification of tear film images captured with the Doane interferometer. The interference phenomena in these images can be characterized as texture patterns, which can be automatically classified into one of the following categories: strong fringes, coalescing strong fringes, fine fringes, coalescing fine fringes, and debris. This work presents a method for classifying tear film images based on texture analysis using phylogenetic diversity indexes and Ripley's K function. The proposed method consists of six main steps: acquisition of the image dataset; segmentation of the region of interest; feature extraction using phylogenetic diversity indexes and Ripley's K function; feature selection using Greedy Stepwise; classification using the algorithms Support Vector Machine (SVM), Random Forest (RF), Naive Bayes (NB), Multilayer Perceptron (MLP), Random Tree (RT) and Radial Basis Function Network (RBFNet); and (6) validation of results. The best result, using the RF classifier, we obtained classification rates higher than 99% of accuracy with 0.843% of standard deviation, 0.999 of the area under the Receiver Operating Characteristics (ROC) curve, 0.995 of Kappa and 0.996 of F-Measure. The experimental results demonstrate that the proposed method is promising and can potentially be used by experts to accurately diagnose dry eye syndrome in tear film images.

journal_name

IEEE J Biomed Health Inform

journal_title

IEEE journal of biomedical and health informatics

authors

da Cruz LB,Souza JC,de Paiva AC,de Almeida JDS,Junior GB,Aires KRT,Silva AC,Gattass M

doi

10.1109/JBHI.2020.3026940

subject

Has Abstract

pub_date

2020-12-01 00:00:00

pages

3491-3498

issue

12

eissn

2168-2194

issn

2168-2208

journal_volume

24

pub_type

杂志文章

相关文献

IEEE Journal of Biomedical and Health Informatics文献大全
  • Groupwise Multichannel Image Registration.

    abstract：:Multichannel image registration is an important challenge in medical image analysis. Multichannel images result from modalities such as dual-energy CT or multispectral microscopy. Besides, multichannel feature images can be derived from acquired images, for instance, by applying multiscale feature banks to the origina...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2018.2844361

    authors： Guyader JM,Huizinga W,Fortunati V,Poot DHJ,Veenland JF,Paulides MM,Niessen WJ,Klein S

    更新日期：2019-05-01 00:00:00

  • Self-Powered Multiparameter Health Sensor.

    abstract：:Wearable health sensors are about to change our health system. While several technological improvements have been presented to enhance performance and energy-efficiency, battery runtime is still a critical concern for practical use of wearable biomedical sensor systems. The runtime limitation is directly related to th...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2708041

    authors： Tobola A,Leutheuser H,Pollak M,Spies P,Hofmann C,Weigand C,Eskofier BM,Fischer G

    更新日期：2018-01-01 00:00:00

  • Automatic Analysis of Food Intake and Meal Microstructure Based on Continuous Weight Measurements.

    abstract：:The structure of the cumulative food intake (CFI) curve has been associated with obesity and eating disorders. Scales that record the weight loss of a plate from which a subject eats food are used for capturing this curve; however, their measurements are contaminated by additive noise and are distorted by certain type...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2018.2812243

    authors： Papapanagiotou V,Diou C,Ioakimidis I,Sodersten P,Delopoulos A

    更新日期：2019-03-01 00:00:00

  • Histopathological Image Classification With Color Pattern Random Binary Hashing-Based PCANet and Matrix-Form Classifier.

    abstract：:The computer-aided diagnosis for histopathological images has attracted considerable attention. Principal component analysis network (PCANet) is a novel deep learning algorithm for feature learning with the simple network architecture and parameters. In this study, a color pattern random binary hashing-based PCANet (C...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2016.2602823

    authors： Shi J,Wu J,Li Y,Zhang Q,Ying S

    更新日期：2017-09-01 00:00:00

  • Detecting Parkinsonian Tremor From IMU Data Collected in-the-Wild Using Deep Multiple-Instance Learning.

    abstract：:Parkinson's Disease (PD) is a slowly evolving neurological disease that affects about [Formula: see text] of the population above 60 years old, causing symptoms that are subtle at first, but whose intensity increases as the disease progresses. Automated detection of these symptoms could offer clues as to the early ons...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2961748

    authors： Papadopoulos A,Kyritsis K,Klingelhoefer L,Bostanjopoulou S,Chaudhuri KR,Delopoulos A

    更新日期：2020-09-01 00:00:00

  • Assessment of Signal Processing Methods for Measuring the Respiratory Rate in the Neonatal Intensive Care Unit.

    abstract：:Knowledge of the pathological instabilities in the breathing pattern can provide valuable insights into the cardiorespiratory status of the critically-ill infant as well as their maturation level. This paper is concerned with the measurement of respiratory rate in premature infants. We compare the rates estimated from...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2898273

    authors： Jorge J,Villarroel M,Chaichulee S,Green G,McCormick K,Tarassenko L

    更新日期：2019-11-01 00:00:00

  • 40-Hz ASSR for Measuring Depth of Anaesthesia During Induction Phase.

    abstract：:This paper proposes an anaesthesia monitoring system that accurately measures the depth of anaesthesia through 40-Hz auditory steady-state response. With accurate and fast depth of anaesthesia measuring, the monitor can reduce the incidence of awareness during surgical operation. The proposed denoising method for extr...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2778140

    authors： Haghighi SJ,Komeili M,Hatzinakos D,Beheiry HE

    更新日期：2018-11-01 00:00:00

  • Detecting Suspected Pump Thrombosis in Left Ventricular Assist Devices via Acoustic Analysis.

    abstract：OBJECTIVE:Left ventricular assist devices (LVADs) fail in up to 10% of patients due to the development of pump thrombosis. Remote monitoring of patients with LVADs can enable early detection and, subsequently, treatment and prevention of pump thrombosis. We assessed whether acoustical signals measured on the chest of p...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2966178

    authors： Semiz B,Hersek S,Pouyan MB,Partida C,Blazquez-Arroyo L,Selby V,Wieselthaler G,Rehg JM,Klein L,Inan OT

    更新日期：2020-07-01 00:00:00

  • Screening For Depression With Retrospectively Harvested Private Versus Public Text.

    abstract：:Depression is the leading cause of disability, often undiagnosed, and one of the most treatable mood disorders. As such, unobtrusively diagnosing depression is important. Many studies are starting to utilize machine learning for depression sensing from social media and Smartphone data to replace the survey instruments...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2983035

    authors： Tlachac ML,Rundensteiner E

    更新日期：2020-11-01 00:00:00

  • Understanding the Physiological Significance of Four Inertial Gait Features in Multiple Sclerosis.

    abstract：:Gait impairment in multiple sclerosis (MS) can result from muscle weakness, physical fatigue, lack of coordination, and other symptoms. Walking speed, as measured by a number of clinician-administered walking tests, is the primary measure of gait impairment used by clinical researchers, but inertial gait features from...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2773629

    authors： Dandu SR,Engelhard MM,Qureshi A,Gong J,Lach JC,Brandt-Pearce M,Goldman MD

    更新日期：2018-01-01 00:00:00

  • Deep Learning for Health Informatics.

    abstract：:With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on machine learning in health informatics. Deep learning, a technique with its founda...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章,评审

    doi：10.1109/JBHI.2016.2636665

    authors： Ravi D,Wong C,Deligianni F,Berthelot M,Andreu-Perez J,Lo B,Yang GZ

    更新日期：2017-01-01 00:00:00

  • Classification and Quantification of Emphysema Using a Multi-Scale Residual Network.

    abstract：:Automated tissue classification is an essential step for quantitative analysis and treatment of emphysema. Although many studies have been conducted in this area, there still remain two major challenges. First, different emphysematous tissue appears in different scales, which we call "inter-class variations." Second, ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2018.2890045

    authors： Peng L,Lin L,Hu H,Li H,Chen Q,Ling X,Wang D,Han X,Iwamoto Y,Chen YW

    更新日期：2019-11-01 00:00:00

  • Modeling of Heart Rate Variability and Respiratory Muscle Activity in Organophosphate Poisoned Patients.

    abstract：:We propose an extended model of cardiovascular regulation to assess heart rate variability in patients poisoned with organophosphate during their treatment with mechanical ventilation. The model was modified to fit a population of 21 patients poisoned with organophosphorus compounds and undergoing mechanical ventilati...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2894758

    authors： Salazar MB,Mauricio Hernandez A,Mananas MA,Cortes Daza C

    更新日期：2019-11-01 00:00:00

  • A Framework for Classifying Online Mental Health-Related Communities With an Interest in Depression.

    abstract：:Mental illness has a deep impact on individuals, families, and by extension, society as a whole. Social networks allow individuals with mental disorders to communicate with others sufferers via online communities, providing an invaluable resource for studies on textual signs of psychological health problems. Mental di...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2016.2543741

    authors： Saha B,Nguyen T,Phung D,Venkatesh S

    更新日期：2016-07-01 00:00:00

  • Network-based modeling and intelligent data mining of social media for improving care.

    abstract：:Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2336251

    authors： Akay A,Dragomir A,Erlandsson BE

    更新日期：2015-01-01 00:00:00

  • A MDP model for breast and ovarian cancer intervention strategies for BRCA1/2 mutation carriers.

    abstract：PURPOSE:Women with BRCA1/2 mutations have higher risk for breast and ovarian cancers. Available intervention actions include prophylactic surgeries and breast screening, which vary significantly in cost, cancer prevention, and in resulting death from other causes. We present a model designed to yield optimal interventi...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2319246

    authors： Abdollahian M,Das TK

    更新日期：2015-03-01 00:00:00

  • Q-Rank: Reinforcement Learning for Recommending Algorithms to Predict Drug Sensitivity to Cancer Therapy.

    abstract：:In personalized medicine, a challenging task is to identify the most effective treatment for a patient. In oncology, several computational models have been developed to predict the response of drugs to therapy. However, the performance of these models depends on multiple factors. This paper presents a new approach, ca...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3004663

    authors： Daoud S,Mdhaffar A,Jmaiel M,Freisleben B

    更新日期：2020-11-01 00:00:00

  • Statistical Metamodeling and Sequential Design of Computer Experiments to Model Glyco-Altered Gating of Sodium Channels in Cardiac Myocytes.

    abstract：:Glycan structures account for up to 35% of the mass of cardiac sodium ( Nav ) channels. To question whether and how reduced sialylation affects Nav activity and cardiac electrical signaling, we conducted a series of in vitro experiments on ventricular apex myocytes under two different glycosylation conditions, reduced...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2458791

    authors： Du D,Yang H,Ednie AR,Bennett ES

    更新日期：2016-09-01 00:00:00

  • Enhancing Predictive Accuracy of Cardiac Autonomic Neuropathy Using Blood Biochemistry Features and Iterative Multitier Ensembles.

    abstract：:Blood biochemistry attributes form an important class of tests, routinely collected several times per year for many patients with diabetes. The objective of this study is to investigate the role of blood biochemistry for improving the predictive accuracy of the diagnosis of cardiac autonomic neuropathy (CAN) progressi...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2363177

    authors： Abawajy J,Kelarev A,Chowdhury MU,Jelinek HF

    更新日期：2016-01-01 00:00:00

  • Cooperative Low-Rank Models for Removing Stripe Noise From OCTA Images.

    abstract：:Optical coherence tomography angiography (OCTA) is an emerging non-invasive imaging technique for imaging the microvasculature of the eye based on phase variance or amplitude decorrelation derived from repeated OCT images of the same tissue area. Stripe noise occurs during the OCTA acquisition process due to the invol...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2997381

    authors： Wu X,Gao D,Borroni D,Madhusudhan S,Jin Z,Zheng Y

    更新日期：2020-12-01 00:00:00

  • Deep Learning for Hemorrhagic Lesion Detection and Segmentation on Brain CT Images.

    abstract：:Stroke is an acute cerebral vascular disease that is likely to cause long-term disabilities and death. Immediate emergency care with accurate diagnosis of computed tomographic (CT) images is crucial for dealing with a hemorrhagic stroke. However, due to the high variability of a stroke's location, contrast, and shape,...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3028243

    authors： Li L,Wei M,Liu B,Atchaneeyasakul K,Zhou F,Pan Z,Kumar S,Zhang J,Pu Y,Liebeskind DS,Scalzo F

    更新日期：2020-10-01 00:00:00

  • Red blood cell cluster separation from digital images for use in sickle cell disease.

    abstract：:The study of cell morphology is an important aspect of the diagnosis of some diseases, such as sickle cell disease, because red blood cell deformation is caused by these diseases. Due to the elongated shape of the erythrocyte, ellipse adjustment and concave point detection are applied widely to images of peripheral bl...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2356402

    authors： González-Hidalgo M,Guerrero-Peña FA,Herold-García S,Jaume-I-Capó A,Marrero-Fernández PD

    更新日期：2015-07-01 00:00:00

  • Neonatal Heart and Lung Sound Quality Assessment for Robust Heart and Breathing Rate Estimation for telehealth Applications.

    abstract：:With advances in digital stethoscopes, internet of things, signal processing and machine learning, chest sounds can be easily collected and transmitted to the cloud for remote monitoring and diagnosis. However, low quality of recordings complicates remote monitoring and diagnosis, particularly for neonatal care. This ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3047602

    authors： Grooby E,He J,Kiewsky J,Fattahi D,Zhou L,King A,Ramanathan A,Malhotra A,Dumont GA,Marzbanrad F

    更新日期：2020-12-28 00:00:00

  • Three-Dimensional Needle Shape Estimation in TRUS-Guided Prostate Brachytherapy Using 2-D Ultrasound Images.

    abstract：:In this paper, we propose an automated method to reconstruct the three-dimensional (3-D) needle shape during needle insertion procedures using only 2-D transverse ultrasound (US) images. Using a set of transverse US images, image processing and random sample consensus are used to locate the needle within each image an...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2477829

    authors： Waine M,Rossa C,Sloboda R,Usmani N,Tavakoli M

    更新日期：2016-11-01 00:00:00

  • Predicting Mood Changes in Bipolar Disorder through Heartbeat Nonlinear Dynamics.

    abstract：:Bipolar Disorder (BD) is characterized by an alternation of mood states from depression to (hypo)mania. Mixed states, i.e., a combination of depression and mania symptoms at the same time, can also be present. The diagnosis of this disorder in the current clinical practice is based only on subjective interviews and qu...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2016.2554546

    authors： Valenza G,Nardelli M,Lanata' A,Gentili C,Bertschy G,Kosel M,Scilingo EP

    更新日期：2016-07-01 00:00:00

  • A low-complexity ECG feature extraction algorithm for mobile healthcare applications.

    abstract：:This paper introduces a low-complexity algorithm for the extraction of the fiducial points from the Electrocardiogram (ECG). The application area we consider is that of remote cardiovascular monitoring, where continuous sensing and processing takes place in low-power, computationally constrained devices, thus the powe...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/TITB.2012.2231312

    authors： Mazomenos EB,Biswas D,Acharyya A,Chen T,Maharatna K,Rosengarten J,Morgan J,Curzen N

    更新日期：2013-03-01 00:00:00

  • DR-GAN: Conditional Generative Adversarial Network for Fine-Grained Lesion Synthesis on Diabetic Retinopathy Images.

    abstract：:Diabetic retinopathy (DR) is a complication of diabetes that severely affects eyes. It can be graded into five levels of severity according to international protocol. However, optimizing a grading model to have strong generalizability requires a large amount of balanced training data, which is difficult to collect, pa...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3045475

    authors： Zhou Y,Wang B,He X,Cui S,Shao L

    更新日期：2020-12-17 00:00:00

  • Predicting Neonatal Sepsis Using Features of Heart Rate Variability, Respiratory Characteristics, and ECG-Derived Estimates of Infant Motion.

    abstract：:This study in preterm infants was designed to characterize the prognostic potential of several features of heart rate variability (HRV), respiration, and (infant) motion for the predictive monitoring of late-onset sepsis (LOS). In a neonatal intensive care setting, the cardiorespiratory waveforms of infants with blood...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2927463

    authors： Joshi R,Kommers D,Oosterwijk L,Feijs L,van Pul C,Andriessen P

    更新日期：2020-03-01 00:00:00

  • Delineation of Electrocardiograms Using Multiscale Parameter Estimation.

    abstract：:The continuing interest in unobtrusive electrocardiography requires the development of algorithms, compensating for an increased number of artifacts. In previous work, we proposed a framework for robust parameter estimation of signals following a piecewise Gaussian derivative model, well suited for describing all wave...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2963786

    authors： Spicher N,Kukuk M

    更新日期：2020-08-01 00:00:00

  • An innovative nonintrusive driver assistance system for vital signal monitoring.

    abstract：:This paper describes an in-vehicle nonintrusive biopotential measurement system for driver health monitoring and fatigue detection. Previous research has found that the physiological signals including eye features, electrocardiography (ECG), electroencephalography (EEG) and their secondary parameters such as heart rat...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2305403

    authors： Sun Y,Yu XB

    更新日期：2014-11-01 00:00:00