An Efficient Framework for Automated Screening of Clinically Significant Macular Edema

01/20/2020
by   Renoh Johnson Chalakkal, et al.
17

The present study proposes a new approach to automated screening of Clinically Significant Macular Edema (CSME) and addresses two major challenges associated with such screenings, i.e., exudate segmentation and imbalanced datasets. The proposed approach replaces the conventional exudate segmentation based feature extraction by combining a pre-trained deep neural network with meta-heuristic feature selection. A feature space over-sampling technique is being used to overcome the effects of skewed datasets and the screening is accomplished by a k-NN based classifier. The role of each data-processing step (e.g., class balancing, feature selection) and the effects of limiting the region-of-interest to fovea on the classification performance are critically analyzed. Finally, the selection and implication of operating point on Receiver Operating Characteristic curve are discussed. The results of this study convincingly demonstrate that by following these fundamental practices of machine learning, a basic k-NN based classifier could effectively accomplish the CSME screening.

READ FULL TEXT

page 1

page 3

research
02/03/2014

Applying Supervised Learning Algorithms and a New Feature Selection Method to Predict Coronary Artery Disease

From a fresh data science perspective, this thesis discusses the predict...
research
06/09/2021

Cervical Cytology Classification Using PCA GWO Enhanced Deep Features Selection

Cervical cancer is one of the most deadly and common diseases among wome...
research
03/16/2023

A Multimodal Data-driven Framework for Anxiety Screening

Early screening for anxiety and appropriate interventions are essential ...
research
09/14/2018

Are screening methods useful in feature selection? An empirical study

Filter or screening methods are often used as a preprocessing step for r...
research
11/01/2014

A Two-phase Decision Support Framework for the Automatic Screening of Digital Fundus Images

In this paper we give a brief review on the present status of automated ...
research
04/07/2021

Online Feature Screening for Data Streams with Concept Drift

Screening feature selection methods are often used as a preprocessing st...
research
03/27/2019

Stable prediction with radiomics data

Motivation: Radiomics refers to the high-throughput mining of quantitati...

Please sign up or login with your details

Forgot password? Click here to reset