Md Abulkalam Azad

Md Abulkalam Azad

he/him

PhD Candidate in Ultrasound Medical Imaging at the Norwegian University of Science and Technology (NTNU)

EchoTracker

EchoTracker is the official implementation of the paper “EchoTracker: Advancing Myocardial Point Tracking in Echocardiography”, published at MICCAI 2024 (early accepted, top 11%).

Overview

EchoTracker is a deep learning framework for long-range myocardial point tracking in 2D echocardiographic sequences. It enables accurate tracking of tissue points across full cardiac cycles, providing a foundation for automated myocardial strain analysis — a clinically important measure of cardiac function.

Key Features

  • Long-range point tracking tailored for echocardiography
  • Robust to cardiac motion, image noise, and temporal variation
  • Enables downstream strain estimation across cardiac views
  • State-of-the-art performance on echocardiographic benchmarks

Technologies

  • Python, PyTorch
  • Deep learning-based optical flow and point tracking
  • Medical image processing