{
  "id": 510345,
  "title": "Improvement using coordinates data",
  "url": "/competitions/rsna-2024-lumbar-spine-degenerative-classification/discussion/510345",
  "author_name": "",
  "post_date": "2024-06-05T19:58:26.203947Z",
  "votes": 7,
  "comment_count": 10,
  "views": 0,
  "content": "<p>I've trained models to predict coordinates of all levels of the spine needed for this competition but I haven't figured out a way to use them to improve score. I've tried adding masks around the predicted x, y coords as channels (6 channel image of the form [original_image, mask1, mask2, mask3, mask4, mask5]) and also cropping out each level and passing in 5 channel image with each level [level1_crop, level2_crop, …, level5_crop] but no improvement in CV. Maybe the model has already learned these features without needing coordinates. Has anyone used the coordinate data to improve their score?</p>",
  "messages": [
    {
      "id": "2857320",
      "postDate": "06/05/2024 19:58:26",
      "content": "<p>I've trained models to predict coordinates of all levels of the spine needed for this competition but I haven't figured out a way to use them to improve score. I've tried adding masks around the predicted x, y coords as channels (6 channel image of the form [original_image, mask1, mask2, mask3, mask4, mask5]) and also cropping out each level and passing in 5 channel image with each level [level1_crop, level2_crop, …, level5_crop] but no improvement in CV. Maybe the model has already learned these features without needing coordinates. Has anyone used the coordinate data to improve their score?</p>",
      "rawMarkdown": "I've trained models to predict coordinates of all levels of the spine needed for this competition but I haven't figured out a way to use them to improve score. I've tried adding masks around the predicted x, y coords as channels (6 channel image of the form [original_image, mask1, mask2, mask3, mask4, mask5]) and also cropping out each level and passing in 5 channel image with each level [level1_crop, level2_crop, ..., level5_crop] but no improvement in CV. Maybe the model has already learned these features without needing coordinates. Has anyone used the coordinate data to improve their score?",
      "votes": null
    },
    {
      "id": "2858872",
      "postDate": "06/06/2024 17:31:58",
      "content": "<p>I will try this and tell you. Are you training multiple models for each condition?</p>",
      "rawMarkdown": "I will try this and tell you. Are you training multiple models for each condition?",
      "votes": null
    },
    {
      "id": "2871583",
      "postDate": "06/14/2024 09:23:42",
      "content": "<p>In the test set there are no instance position where the stenosis can be found unlike in the train label coordinate csv file, how I go about this.</p>",
      "rawMarkdown": "In the test set there are no instance position where the stenosis can be found unlike in the train label coordinate csv file, how I go about this.",
      "votes": null
    },
    {
      "id": "2871639",
      "postDate": "06/14/2024 10:03:44",
      "content": "<p>train models to predict it or just discard it</p>",
      "rawMarkdown": "train models to predict it or just discard it",
      "votes": null
    },
    {
      "id": "2871690",
      "postDate": "06/14/2024 10:44:39",
      "content": "<p>What kinds of masks do you use? Have you ever thought of the shift invariance in CNN model?</p>",
      "rawMarkdown": "What kinds of masks do you use? Have you ever thought of the shift invariance in CNN model?",
      "votes": null
    },
    {
      "id": "2872436",
      "postDate": "06/14/2024 19:07:56",
      "content": "<p>please cold you walk me throught the process  of makign predictions on the test images dataset</p>",
      "rawMarkdown": "please cold you walk me throught the process  of makign predictions on the test images dataset",
      "votes": null
    },
    {
      "id": "2877248",
      "postDate": "06/18/2024 09:03:20",
      "content": "<p>You can either train a segmentation model by creating masks using x and y or, you can train an object detection model by creating bounding boxes using x and y</p>",
      "rawMarkdown": "You can either train a segmentation model by creating masks using x and y or, you can train an object detection model by creating bounding boxes using x and y",
      "votes": null
    },
    {
      "id": "2877332",
      "postDate": "06/18/2024 09:52:16",
      "content": "<p>the question is that the masks we created may not be accurate enough. any idea?</p>",
      "rawMarkdown": "the question is that the masks we created may not be accurate enough. any idea?",
      "votes": null
    },
    {
      "id": "2878513",
      "postDate": "06/19/2024 02:47:36",
      "content": "<p>That's the challenge. Am experimenting with different ranges for the radius, here is how am trying to create rectangular or circular masks; (x-radius, y-radius), (x+radius, y+radius)</p>",
      "rawMarkdown": "That's the challenge. Am experimenting with different ranges for the radius, here is how am trying to create rectangular or circular masks; (x-radius, y-radius), (x+radius, y+radius)",
      "votes": null
    },
    {
      "id": "2878979",
      "postDate": "06/19/2024 09:48:01",
      "content": "<p>sounds good. maybe we can also try different shapes of masks</p>",
      "rawMarkdown": "sounds good. maybe we can also try different shapes of masks",
      "votes": null
    },
    {
      "id": "2883456",
      "postDate": "06/22/2024 02:13:54",
      "content": "<p>I tried to use the coordinate to make a frame as ROI.  but i later realized that coordinates are not provided in test set.</p>",
      "rawMarkdown": "I tried to use the coordinate to make a frame as ROI.  but i later realized that coordinates are not provided in test set.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2858872,
      "author_name": "manaidu",
      "author_url": "",
      "post_date": "06/06/2024 17:31:58",
      "content": "<p>I will try this and tell you. Are you training multiple models for each condition?</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 2871583,
      "author_name": "theexaltedone",
      "author_url": "",
      "post_date": "06/14/2024 09:23:42",
      "content": "<p>In the test set there are no instance position where the stenosis can be found unlike in the train label coordinate csv file, how I go about this.</p>",
      "votes": null,
      "replies": [
        {
          "id": 2871639,
          "author_name": "kidougen",
          "author_url": "",
          "post_date": "06/14/2024 10:03:44",
          "content": "<p>train models to predict it or just discard it</p>",
          "votes": null,
          "replies": [
            {
              "id": 2872436,
              "author_name": "theexaltedone",
              "author_url": "",
              "post_date": "06/14/2024 19:07:56",
              "content": "<p>please cold you walk me throught the process  of makign predictions on the test images dataset</p>",
              "votes": null,
              "replies": [
                {
                  "id": 2877248,
                  "author_name": "samu2505",
                  "author_url": "",
                  "post_date": "06/18/2024 09:03:20",
                  "content": "<p>You can either train a segmentation model by creating masks using x and y or, you can train an object detection model by creating bounding boxes using x and y</p>",
                  "votes": null,
                  "replies": [
                    {
                      "id": 2877332,
                      "author_name": "kidougen",
                      "author_url": "",
                      "post_date": "06/18/2024 09:52:16",
                      "content": "<p>the question is that the masks we created may not be accurate enough. any idea?</p>",
                      "votes": null,
                      "replies": [
                        {
                          "id": 2878513,
                          "author_name": "samu2505",
                          "author_url": "",
                          "post_date": "06/19/2024 02:47:36",
                          "content": "<p>That's the challenge. Am experimenting with different ranges for the radius, here is how am trying to create rectangular or circular masks; (x-radius, y-radius), (x+radius, y+radius)</p>",
                          "votes": null,
                          "replies": [
                            {
                              "id": 2878979,
                              "author_name": "kidougen",
                              "author_url": "",
                              "post_date": "06/19/2024 09:48:01",
                              "content": "<p>sounds good. maybe we can also try different shapes of masks</p>",
                              "votes": null,
                              "replies": []
                            }
                          ]
                        }
                      ]
                    }
                  ]
                }
              ]
            }
          ]
        }
      ]
    },
    {
      "id": 2871690,
      "author_name": "shipuxu",
      "author_url": "",
      "post_date": "06/14/2024 10:44:39",
      "content": "<p>What kinds of masks do you use? Have you ever thought of the shift invariance in CNN model?</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 2883456,
      "author_name": "jackysywk",
      "author_url": "",
      "post_date": "06/22/2024 02:13:54",
      "content": "<p>I tried to use the coordinate to make a frame as ROI.  but i later realized that coordinates are not provided in test set.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2857320": "I've trained models to predict coordinates of all levels of the spine needed for this competition but I haven't figured out a way to use them to improve score. I've tried adding masks around the predicted x, y coords as channels (6 channel image of the form [original_image, mask1, mask2, mask3, mask4, mask5]) and also cropping out each level and passing in 5 channel image with each level [level1_crop, level2_crop, ..., level5_crop] but no improvement in CV. Maybe the model has already learned these features without needing coordinates. Has anyone used the coordinate data to improve their score?",
    "2858872": "I will try this and tell you. Are you training multiple models for each condition?",
    "2871583": "In the test set there are no instance position where the stenosis can be found unlike in the train label coordinate csv file, how I go about this.",
    "2871639": "train models to predict it or just discard it",
    "2871690": "What kinds of masks do you use? Have you ever thought of the shift invariance in CNN model?",
    "2872436": "please cold you walk me throught the process  of makign predictions on the test images dataset",
    "2877248": "You can either train a segmentation model by creating masks using x and y or, you can train an object detection model by creating bounding boxes using x and y",
    "2877332": "the question is that the masks we created may not be accurate enough. any idea?",
    "2878513": "That's the challenge. Am experimenting with different ranges for the radius, here is how am trying to create rectangular or circular masks; (x-radius, y-radius), (x+radius, y+radius)",
    "2878979": "sounds good. maybe we can also try different shapes of masks",
    "2883456": "I tried to use the coordinate to make a frame as ROI.  but i later realized that coordinates are not provided in test set."
  },
  "source": "meta"
}