Life Sciences & Biotechnology
Title : | An automated lung ultrasound workflow for diagnostic assistance in COVID-19 and beyond |
Area of research : | COVID-19 Research, Life Sciences & Biotechnology |
Focus area : | COVID-19 Diagnostics |
Principal Investigator : | Dr Mahesh Raveendranatha Panicker, Assistant Professor, Indian Institute of Technology (IIT) Palakkad |
Timeline Start Year : | 2020 |
Timeline End Year : | 2020 |
Contact info : | mahesh@iitpkd.ac.in |
Details
Executive Summary : | The approach of this study is to analyse Lung ultrasonography (LUS) images over cloud, to score each image according to the severity of infection based on certain reported signatures in literature and to track the progress of infection over different days. |
Outcome/Output: | LUS has the added advantage of ease of use at point of care, repeatability, absence of radiation exposure, and low cost. A lightweight algorithm based on You look only once version 5 (YOLO5) and single shot detection (SSD) has been developed that has the capability of providing the quality of images based on the identification of various LUS landmarks, prediction of severity of lung infection and possibility of active learning based on the feedback from clinicians. |
Organizations involved