Back close
Admissions

Deep Learning based Automated ASPECT Score and Infarct Core Prediction for Stroke Patients

Start Date: Wednesday, Mar 01,2023

End Date: Monday, Mar 31,2025

Project Incharge:Dr. Vivek Menon
Co-Project Incharge:Dr. Vivek Nambiar, Dr. Sudheeran Kannoth, Dr. Prema Nedungadi
Funded by:ICMR
Deep Learning based Automated ASPECT Score and Infarct Core Prediction for Stroke Patients

The onset of ischemic stroke can be attributed to large vessel occlusions (LVOs), which lead to insufficient supply of oxygen to brain. Early detection and evaluation of infarct core volume plays a crucial role in the optimal treatment for brain ischemia. Leveraging state of the art Deep Learning techniques on Non-Contrast CT (NCCT) brain scans of patients affected by ischemic stroke, our goals are to 

  • automate computing of Alberta Stroke ProgramEarly CT Score (ASPECT Score)
  • automate the segmentation of the infarct core
  • generate Cerebral Blood Volume (CBV) perfusion maps.

Related Projects

Sameekshanam – Be Calm, Be Compassionate 
Sameekshanam – Be Calm, Be Compassionate 
Synthesis and Characterization of Novel Porphyrins with Different Chromophores for Developing Optoelectronic Materials and Devices
Synthesis and Characterization of Novel Porphyrins with Different Chromophores for Developing Optoelectronic Materials and Devices
Isolation and identification of endophytes from marine algae
Isolation and identification of endophytes from marine algae
Isolation and Characterization of Host Binding Proteins from Bacillus Clausii Using Mass Spectrometry-a Proteomic Approach
Isolation and Characterization of Host Binding Proteins from Bacillus Clausii Using Mass Spectrometry-a Proteomic Approach
An exploratory clinical study to determine the utility of heart rate variability analysis in the assessment of dosha imbalance
An exploratory clinical study to determine the utility of heart rate variability analysis in the assessment of dosha imbalance
Admissions Apply Now