{
  "id": 639205,
  "title": "about ECG grid annotation",
  "url": "/competitions/physionet-ecg-image-digitization/discussion/639205",
  "author_name": "",
  "post_date": "2025-11-24T15:11:46.228040600Z",
  "votes": null,
  "comment_count": 1,
  "views": 0,
  "content": "<p>In the case of something like “0001,” we could generate grid annotation data ourselves and use it to train a U-Net. However, how can we annotate crumpled or contaminated sheets? Manually marking them one by one to create training data would be extremely labor-intensive.</p>",
  "messages": [
    {
      "id": "3346665",
      "postDate": "11/24/2025 15:11:46",
      "content": "<p>In the case of something like “0001,” we could generate grid annotation data ourselves and use it to train a U-Net. However, how can we annotate crumpled or contaminated sheets? Manually marking them one by one to create training data would be extremely labor-intensive.</p>",
      "rawMarkdown": "In the case of something like “0001,” we could generate grid annotation data ourselves and use it to train a U-Net. However, how can we annotate crumpled or contaminated sheets? Manually marking them one by one to create training data would be extremely labor-intensive.",
      "votes": null
    },
    {
      "id": "3348475",
      "postDate": "11/25/2025 23:01:41",
      "content": "<p>Well, no way around that, unless you decide to use a synthetic ECG data generator, one such as: <a href=\"https://github.com/alphanumericslab/ecg-image-kit\" target=\"_blank\">ECG-Image-Kit</a> to generate samples you need</p>\n<p>You can even create your own synthesizer if you really want to as it can give you better control on the kind of things to generate alongside your samples, like segmentation masks</p>",
      "rawMarkdown": "Well, no way around that, unless you decide to use a synthetic ECG data generator, one such as: [ECG-Image-Kit](https://github.com/alphanumericslab/ecg-image-kit) to generate samples you need\n\nYou can even create your own synthesizer if you really want to as it can give you better control on the kind of things to generate alongside your samples, like segmentation masks",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 3348475,
      "author_name": "henrychibueze",
      "author_url": "",
      "post_date": "11/25/2025 23:01:41",
      "content": "<p>Well, no way around that, unless you decide to use a synthetic ECG data generator, one such as: <a href=\"https://github.com/alphanumericslab/ecg-image-kit\" target=\"_blank\">ECG-Image-Kit</a> to generate samples you need</p>\n<p>You can even create your own synthesizer if you really want to as it can give you better control on the kind of things to generate alongside your samples, like segmentation masks</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "3346665": "In the case of something like “0001,” we could generate grid annotation data ourselves and use it to train a U-Net. However, how can we annotate crumpled or contaminated sheets? Manually marking them one by one to create training data would be extremely labor-intensive.",
    "3348475": "Well, no way around that, unless you decide to use a synthetic ECG data generator, one such as: [ECG-Image-Kit](https://github.com/alphanumericslab/ecg-image-kit) to generate samples you need\n\nYou can even create your own synthesizer if you really want to as it can give you better control on the kind of things to generate alongside your samples, like segmentation masks"
  },
  "source": "meta"
}