IMC 2 Lab
Multi-Modal Feature Fusion for Myocardial Infarction Detection
Echo/MRI-Based Pipeline for Cardiac Abnormality Detection
Dr Shahryar Najam Ayesha Qaiser Hashmi Affia Ahmed Haleema Rehman Abdullah Iftikhar
Project Overview
A multi-modal feature fusion pipeline for myocardial infarction detection from echocardiogram and MRI sequences using deep learning. The system extracts complementary features from both imaging modalities, fuses them through attention-guided mechanisms, and classifies cardiac abnormalities with high sensitivity and specificity, enabling early detection of heart attacks and improved patient outcomes in clinical cardiology.
System Architecture
Inputs
Echo
MRI
Processing Pipeline
Feature Extraction
Attention Fusion
Classifier
Outputs
MI Diagnosis
Risk Score
Related Publications (8)
Curated from publications by Dr. Shaheryar Najam
2026journal
CrowdVoxel-Net: Voxelized Geometry and Transformer-Based Multimodal Fusion for Activity Recognition and Anomaly Detection in UAV-Based Crowded Scenes
Egyptian Informatics Journal, 2026
View on Scholar2025conference
Multimodal 2.5D Feature Fusion and LSTM Classifier for Telerehabilitation
ICIC25, 2025
View on Scholar2026journal
Transformer-Driven Multimodal for Human-Object Detection and Recognition for Intelligent Robotic Surveillance
Computers, Materials, & Continua 87 (1), 2026
View on Scholar2026journal
ACO-Optimized Multi-Feature Fusion Integrating Hand Pose Estimation and Shape Descriptors for Sign Language Classification
KHI HTC 2026, 2026
View on Scholar2026journal
Multi-Level Feature Fusion and Graph-Based Contextual Modeling for Accurate Skin Cancer Classification
KHI HTC 2026, 2026
View on Scholar2025conference
Hand Gesture Recognition via GNN Attention-Keypoint Features Fusion and Geometric Encoding
HITE25, 2025
View on Scholar2025journal
Two-hand static and dynamic Arabic sign language recognition using keypoints and shape descriptors with attention-driven feature fusion
PeerJ CS, 2025
View on Scholar2026journal
Robust Multi-Modal Hand-Object Interaction via Hybrid Features and Graph Neural Network on Egocentric Dataset
KHI HTC 2026, 2026
View on Scholar

