Abstract
Glomerulosclerosis is a pathomorphological feature of glomerular lesions. Early detection, accurate judgement and effective prevention of the glomeruli is crucial not only for people with kidney disease, but also for the general population. We proposed a method in combination of traditional image analysis with modern machine learning diagnosis system model based on GoogLeNet for recognizing and distinguishing different categories of glomerulus in order to efficiently capture the important structures as well as to minimize manual effort and supervision. We proposed a novel deep learning model based on GoogLeNet with added batch-normalization layers to extract useful features and subsequently entered the features into SoftMax for classification. We also incorporated Bayesian Optimization algorithm and k-fold cross validation in this system for achieving a more reliable result. Our method has eventually achieved an overall accuracy of 95.04±4.99%, and F1 score of 94.44±3.11% for no glomerulus category, 96.73±5.23% for normal glomerulus category and 93.66±7.82% for globally sclerosed glomerulus category, which means this method can accurately determine the degree of glomerulosclerosis with little supervision. The experimental result also shows that this method has better performance when compared with other state-of art methods.
Highlights
The incidence of chronic kidney disease (CKD) is gradually increasing worldwide and has become one of the most important diseases threatening human health
In this method [33]–[36], the average of the evaluation indexes (Precision/ Recall/ F1 score) of different categories was obtained directly by adding them together, and the same weight was given to all categories
RESULT OF OUR MODEL WITHOUT BAYESIAN OPTIMIZATION In TABLE 3, our comparison experiment results show that if we do not utilize Bayesian optimization algorithm to adjust hyperparameters, the model will achieve an overall accuracy of 88.48±4.66%, and F1 score of 89.80±4.50% for no glomerulus category, 91.77±6.15% for normal glomerulus category and 82.07±13.70% for globally sclerosed (GS) glomerulus category
Summary
The incidence of chronic kidney disease (CKD) is gradually increasing worldwide and has become one of the most important diseases threatening human health. Glomerulosclerosis is a pathomorphological feature of glomerular lesions. This lesion is characterized by sclerosing changes in the glomerular capillary loops. It is clinically known as sclerosing glomerulonephritis, which is a glomerular end-stage disease caused by a variety of diseases. Glomerulosclerosis is an irreversible injury that should arouse wide public concern. According to relevant foreign research data on voluntary
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