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1. ECG_Leads_Detection ECG_Leads_Detection Public

   Jupyter Notebook

2. ecg-dataset-pipeline ecg-dataset-pipeline Public

   Handles dataset creation and organization for ECG analysis. Includes data ingestion, validation, metadata handling, and structured storage for downstream tasks.

   Jupyter Notebook

3. ecg-signal-segmentation ecg-signal-segmentation Public

   Implements segmentation of ECG images into clinically relevant components. Supports lead-wise segmentation to improve feature extraction and model performance.

   Python

4. ecg-digitization ecg-digitization Public

   Converts sgemented ecg images into standardized digital formats and then back to images. Ensures consistency, resolution normalization, and compatibility with machine learning models.

   Python

5. ecg-preprocessing ecg-preprocessing Public

   Performs preprocessing operations such as resizing, normalization, padding, and noise handling. Prepares ECGs for efficient and stable training and inference.

   Jupyter Notebook

6. ecg-image-enhancement ecg-image-enhancement Public

   Applies enhancement techniques to improve ECG image quality and clarity. Focuses on contrast enhancement and noise reduction to boost diagnostic accuracy.

   Python