scholarly journals Automated Grading of Diabetic Retinopathy with Ultra-Widefield Fluorescein Angiography and Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiaoling Wang ◽  
Zexuan Ji ◽  
Xiao Ma ◽  
Ziyue Zhang ◽  
Zuohuizi Yi ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Linear Regression ◽  
Fluorescein Angiography ◽  
Confusion Matrix ◽  
Regression Function ◽  
Diabetic Patients ◽  
Simple Linear Regression ◽  
Generative Adversarial Network ◽  
Data Set ◽  
Linear Regression Function

Purpose. The objective of this study was to establish diagnostic technology to automatically grade the severity of diabetic retinopathy (DR) according to the ischemic index and leakage index with ultra-widefield fluorescein angiography (UWFA) and the Early Treatment Diabetic Retinopathy Study (ETDRS) 7-standard field (7-SF). Methods. This is a cross-sectional study. UWFA samples from 280 diabetic patients and 119 normal patients were used to train and test an artificial intelligence model to differentiate PDR and NPDR based on the ischemic index and leakage index with UWFA. A panel of retinal specialists determined the ground truth for our data set before experimentation. A confusion matrix as a metric was used to measure the precision of our algorithm, and a simple linear regression function was implemented to explore the discrimination of indexes on the DR grades. In addition, the model was tested with simulated 7-SF. Results. The model classification of DR in the original UWFA images achieved 88.50% accuracy and 73.68% accuracy in the simulated 7-SF images. A simple linear regression function demonstrated that there is a significant relationship between the ischemic index and leakage index and the severity of DR. These two thresholds were set to classify the grade of DR, which achieved 76.8% accuracy. Conclusions. The optimization of the cycle generative adversarial network (CycleGAN) and convolutional neural network (CNN) model classifier achieved DR grading based on the ischemic index and leakage index with UWFA and simulated 7-SF and provided accurate inference results. The classification accuracy with UWFA is slightly higher than that of simulated 7-SF.

scholarly journals Automated Detection and Classification of Diabetic Retinopathy using ConvNets

2021 ◽  
Vol 9 (10) ◽  
pp. 1360-1369
Author(s):  
Aavani B
Keyword(s):  
Neural Network ◽  
Diabetic Retinopathy ◽  
Confusion Matrix ◽  
Diabetic Patients ◽  
Fundus Image ◽  
Data Set ◽  
Permanent Loss ◽  
Process Computer ◽  
Degree Classification

Abstract: Diabetic retinopathy is the leading cause of blindness in diabetic patients. Screening of diabetic retinopathy using fundus image is the most effective way. As the time increases this DR leads to permanent loss of vision. At present, Diabetic retinopathy is still being treated by hand by an ophthalmologist which is a time-consuming process. Computer aided and fully automatic diagnosis of DR plays an important role in now a day. Data-set containing a collection of fundus images of different severity scale is used to analyze the fundus image of DR patients. Here the deep neural network model is trained by using this fundus image and five-degree classification task is performed. We were able to produce an sensitivity of 90%. Keywords: Confusion matrix, Deep convolutional Neural Network, Diabetic Retinopathy, Fundus image, OCT

Experimental Study of Short-Term Creep Characteristics Base on Step Loading-Unloading Method for Hard Rock

2013 ◽  
Vol 774-776 ◽  
pp. 86-93
Author(s):  
Fu Jun Zhang ◽  
Chuan Xiao Liu
Keyword(s):  
Linear Regression ◽  
Axial Strain ◽  
Radial Strain ◽  
Strain Curve ◽  
Regression Function ◽  
Nonlinear Creep ◽  
Linear Regression Function ◽  
Term Creep ◽  
Sandstone Specimen ◽  
Short Term Creep

Based on experimental results of uniaxial compression and short-term creep using 8-step loading-unloading method, fine sandstone specimen, which lower creep limit is 27MPa, present typical brittle breakage properties of hard rock. The correlative coefficients of linear regression function for isochronous stress-strain curve are all higher than 0. 92, and the ratio of long-term strength to instantaneous strength reaches 94. 39%，which indicate that the whole creep of fine sandstone specimen is weak. The average correlative coefficients of linear regression function for isochronous stress- axial strain curve are 3. 92% higher than that of average correlative coefficients of linear regression function for isochronous stress- radial strain curve, so nonlinear creep property of the fine sandstone specimen in axial direction is correspondingly weaker than that in radial direction. Negative Gauss distribution can be applied collectively to nonlinear creep of fine sandstone specimen, which has obvious time effect.With increasing loading, the reduction degrees of average correlative coefficients of linear fitting functions of isochronous stress-axial strain curve and isochronous stress-radial strain curve are 0. 97% and 0. 67% respectively, which indicates the linear correlation decreases commonly. Thus, the degree of nonlinear creep for fine sandstone specimen increases along with loading stress with obvious stress effect.

scholarly journals Fundus Fluorescein Angiography and Optical Coherence Tomography Angiography Findings in Diabetic Retinopathy and Diabetic Macular Edema

2018 ◽  
pp. 130-137
Keyword(s):  
Optical Coherence Tomography ◽  
Diabetic Retinopathy ◽  
Fluorescein Angiography ◽  
Macular Edema ◽  
Diabetic Macular Edema ◽  
Optical Coherence Tomography Angiography ◽  
Imaging Technique ◽  
Diabetic Patients ◽  
Type I ◽  
Optical Coherence

Diabetic retinopathy is an important public health issue as its prevalence has been increasing every year. It is one of the major causes of visual loss which can be preventable with early diagnosis and appropriate treatment. The fundus examination must be done in detail using mydriatics, and digital images must be recorded in all diabetic patients with special emphasis on the disease type (type I and type II), duration, and prognosis. Fluorescein angiography (FA) is a gold standard invasive retinal imaging technique for the diagnosis, monitoring, and evaluating the response of the treatment in diabetic patients, but FA has limitations due to possible side effects. Optical coherence tomography angiography (OCTA) is a recent, non-invasive, dye-free imaging technique that can be used in every visit. It has the capability to image all retinal and choroidal vascular layers (segmentation) and quantify macular ischemia in a short period of time which is beneficial for the patient, and the ophthalmologist. The aim of this review is to address the findings, advantages, and disadvantages of FA and OCTA in patients with diabetic retinopathy and diabetic macular edema.

scholarly journals Temperature dependence of blood surface tension

2007 ◽  
pp. S93-S98
Author(s):  
J Rosina ◽  
E Kvašňák ◽  
D Šuta ◽  
H Kolářová ◽  
J Málek ◽  
...  
Keyword(s):  
Surface Tension ◽  
Linear Regression ◽  
Blood Serum ◽  
Whole Blood ◽  
Healthy Subjects ◽  
Regression Function ◽  
Sediment Surface ◽  
Linear Regression Equation ◽  
Linear Regression Function ◽  
Ring Method

Whole blood surface tension of 15 healthy subjects recorded by the ring method was investigated in the temperature range from 20 to 40 degrees C. The surface tension omega as a function of temperature t ( degrees C) is described by an equation of linear regression as omega(t) = (-0.473 t + 70.105) x 10(-3) N/m. Blood serum surface tension in the range from 20 to 40 degrees C is described by linear regression equation omega(t) = (-0.368 t + 66.072) x 10(-3) N/m and linear regression function of blood sediment surface tension is omega(t) = (-0.423 t + 67.223) x10(-3) N/m.

scholarly journals METODA ZANURZANIA REGRESJI W PRZYPADKU WYSTĘPOWANIA OBSERWACJI NIETYPOWYCH

2019 ◽  
Vol 20 (2) ◽  
pp. 83-92
Author(s):  
Małgorzata Kobylińska
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Least Squares Method ◽  
Regression Function ◽  
Maximum Depth ◽  
Two Dimensional ◽  
Structural Elements ◽  
Linear Regression Function ◽  
Regression Functions

This paper presents the application of the regression maximum depth for the estimation of linear regression function structural elements. For two-dimensional sets including untypical observations, regression functions were developed using the classical least squares method and a method based on the concept of observation depth measure in a sample. The effect of untypical observations on the estimated models has been noted.

scholarly journals Pengaruh Citra Bank dan Promosi Undian Ghendis Manis Terhadap Keputusan Petani Tebu Menabung di Bank

2017 ◽  
Vol 1 (1) ◽  
pp. 76-87
Author(s):  
Umar Makruf ◽  
Hesti Budiwati
Keyword(s):  
Linear Regression ◽  
Quantitative Research ◽  
Linear Regression Analysis ◽  
Regression Function ◽  
Multiple Linear Regression Analysis ◽  
Coefficient Of Determination ◽  
Simple Linear Regression ◽  
Effect Relation ◽  
Saving Decisions ◽  
Branch Office

The study aims to knowed influence of bank image and promotion on gamling gendis manis to farming dicision to saving in Lumajang Branch office of BRI. Either partially of simultaneously. This research is quantitative research to find the associative relationship that are causal or the research to ask the question the relations between two or more variable and cause effect relation. The study aims to find evidence of the influence of bank image and promotion on saving decisions of Lumajang Barnch Office of Bank Rakyat Indonesia either partially or simultaneously. This study tested the hypothesis that there is a bank image effect on the saving decisions, there is promotion on saing decisions, and there is the influence of bank image and promotion to work simultaneously on the performance of employees at the National Narcotics Agency office Lumajang. The study, of 45 respondents using multiple linear regression analysis is the bank image there is an influence on saving decisions, there is work promotion on saving decisions, and there is the influence of bank image and promotion to work simultaneously on the decisions of saving at the Lumajang Barnch Office of Bank Rakyat Indonesia. Simple linear regression function generated is Y= 4,096 + 0,345X1 + 0,183X2. The coefficient of determination showed that 53,5 of saving decisions can be explained by the bank image and promotion t, while the remaining 46,5% of saving decisions is influenced by other variables not examined in this study.

scholarly journals Improving PM<sub>2.5</sub> retrievals in the San Joaquin Valley using A-Train Multi-Satellite Observations

2011 ◽  
Vol 11 (11) ◽  
pp. 30563-30598 ◽  
Author(s):  
A. W. Strawa ◽  
R. B. Chatfield ◽  
M. Legg ◽  
B. Scarnato ◽  
R. Esswein
Keyword(s):  
Linear Regression ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Ground Level ◽  
San Joaquin Valley ◽  
Satellite Observations ◽  
Target Area ◽  
Simple Linear Regression ◽  
Data Set ◽  
Modis Aod

Abstract. This paper demonstrates the use of a combination of multi-platform satellite observations and statistical data analysis to dramatically improve the correlation between satellite observed aerosol optical depth (AOD) and ground-level retrieved PM2.5. The target area is California's San Joaquin Valley which has a history of poor particulate air quality and where such correlations have not yielded good results. We have used MODIS AOD, OMI AOD, AAOD (absorption aerosol optical depth) and NO2 concentration, and a seasonal parameter in a generalized additive model (GAM) to improve retrieved/observed PM2.5 correlations (r2 at six individual sites and for a data set combining all sites. For the combined data set using the GAM, r2 improved to 0.69 compared with an r2 of 0.27 for a simple linear regression of MODIS AOD to surface PM. Parameter sensitivities and the effect of multi-platform data on the sample size are discussed. Particularly noteworthy is the fact that the PM retrieved using the GAM captures many of the PM exceedences that were not seen in the simple linear regression model.

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