LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 1 of total 1

Search options

Article: An Explainable AI driven Decision Support System for COVID-19 Diagnosis using Fused Classification and Segmentation.

Niranjan, K / Shankar Kumar, S / Vedanth, S / Chitrakala, Dr S

Procedia computer science

2023  Volume 218, Page(s) 1915–1925

Abstract: The coronavirus has caused havoc on billions of people worldwide. The Reverse Transcription Polymerase Chain Reaction(RT-PCR) test is widely accepted as a standard diagnostic tool for detecting infection, however, the severity of infection can't be ... ...

Abstract The coronavirus has caused havoc on billions of people worldwide. The Reverse Transcription Polymerase Chain Reaction(RT-PCR) test is widely accepted as a standard diagnostic tool for detecting infection, however, the severity of infection can't be measured accurately with RT-PCR results. Chest CT Scans of infected patients can manifest the presence of lesions with high sensitivity. During the pandemic, there is a dearth of competent doctors to examine chest CT images. Therefore, a Guided Gradcam based Explainable Classification and Segmentation system (GGECS) which is a real-time explainable classification and lesion identification decision support system is proposed in this work. The classification model used in the proposed GGECS system is inspired by Res2Net. Explainable AI techniques like GradCam and Guided GradCam are used to demystify Convolutional Neural Networks (CNNs). These explainable systems can assist in localizing the regions in the CT scan that contribute significantly to the system's prediction. The segmentation model can further reliably localize infected regions. The segmentation model is a fusion between the VGG-16 and the classification network. The proposed classification model in GGECS obtains an overall accuracy of 98.51 % and the segmentation model achieves an IoU score of 0.595.
Language English
Publishing date 2023-01-31
Publishing country Netherlands
Document type Journal Article
ZDB-ID 2557358-5
ISSN 1877-0509
ISSN 1877-0509
DOI 10.1016/j.procs.2023.01.168
Database MEDical Literature Analysis and Retrieval System OnLINE

More links

Kategorien

To top