{
  "id": 265164,
  "title": "[Info] Multi-Modal MRI Spatial Alignment Network",
  "url": "/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/265164",
  "author_name": "",
  "post_date": "2021-08-14T20:44:24.353864200Z",
  "votes": 37,
  "comment_count": 6,
  "views": 0,
  "content": "<p>Interesting work </p>\n<p>paper: <a href=\"https://arxiv.org/pdf/2108.05603v1.pdf\" target=\"_blank\">Multi-Modal MRI Reconstruction with Spatial Alignment Network</a><br>\ncode (pytorch): <a href=\"https://github.com/woxuankai/spatialalignmentnetwork\" target=\"_blank\">https://github.com/woxuankai/spatialalignmentnetwork</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/129459567-903797f7-86f3-4ee8-9b37-fb98ec93b8a5.png\" alt=\"Screenshot 2021-08-15 024301\"></p>",
  "messages": [
    {
      "id": "1472404",
      "postDate": "08/14/2021 20:44:24",
      "content": "<p>Interesting work </p>\n<p>paper: <a href=\"https://arxiv.org/pdf/2108.05603v1.pdf\" target=\"_blank\">Multi-Modal MRI Reconstruction with Spatial Alignment Network</a><br>\ncode (pytorch): <a href=\"https://github.com/woxuankai/spatialalignmentnetwork\" target=\"_blank\">https://github.com/woxuankai/spatialalignmentnetwork</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/129459567-903797f7-86f3-4ee8-9b37-fb98ec93b8a5.png\" alt=\"Screenshot 2021-08-15 024301\"></p>",
      "rawMarkdown": "Interesting work \n\npaper: [Multi-Modal MRI Reconstruction with Spatial Alignment Network](https://arxiv.org/pdf/2108.05603v1.pdf)\ncode (pytorch): https://github.com/woxuankai/spatialalignmentnetwork\n\n![Screenshot 2021-08-15 024301](https://user-images.githubusercontent.com/17668390/129459567-903797f7-86f3-4ee8-9b37-fb98ec93b8a5.png)",
      "votes": null
    },
    {
      "id": "1486748",
      "postDate": "08/23/2021 07:42:09",
      "content": "<h2>Transformer on BraTS</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2103.04430v2.pdf\" target=\"_blank\"><strong>TransBTS: Multimodal Brain Tumor Segmentation Using Transformer</strong></a><br>\nCode (pytorch): <a href=\"https://github.com/Wenxuan-1119/TransBTS\" target=\"_blank\">https://github.com/Wenxuan-1119/TransBTS</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130409377-167c3882-8a6c-498f-a2f3-c75624b70170.png\" alt=\"TransBTS\"></p>",
      "rawMarkdown": "## Transformer on BraTS\n\nPaper: [**TransBTS: Multimodal Brain Tumor Segmentation Using Transformer**](https://arxiv.org/pdf/2103.04430v2.pdf)\nCode (pytorch): https://github.com/Wenxuan-1119/TransBTS\n\n![TransBTS](https://user-images.githubusercontent.com/17668390/130409377-167c3882-8a6c-498f-a2f3-c75624b70170.png)",
      "votes": null
    },
    {
      "id": "1486758",
      "postDate": "08/23/2021 07:48:46",
      "content": "<h2>Modeling with Missing Modalities</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2106.14591v2.pdf\" target=\"_blank\"><strong>ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities</strong></a><br>\nCode (pytorch): <a href=\"https://github.com/Wangyixinxin/ACN\" target=\"_blank\">https://github.com/Wangyixinxin/ACN</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130410273-91867cd8-9f3a-4707-ae7d-4ebae82fe17e.png\" alt=\"TransBTS\"></p>",
      "rawMarkdown": "## Modeling with Missing Modalities\n\nPaper: [**ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities**](https://arxiv.org/pdf/2106.14591v2.pdf)\nCode (pytorch): https://github.com/Wangyixinxin/ACN\n\n![TransBTS](https://user-images.githubusercontent.com/17668390/130410273-91867cd8-9f3a-4707-ae7d-4ebae82fe17e.png)",
      "votes": null
    },
    {
      "id": "1486769",
      "postDate": "08/23/2021 07:55:45",
      "content": "<h2>Self-Ensembled (3D Test Time Augmentation)</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2011.01045v2.pdf\" target=\"_blank\"><strong>Brain tumor segmentation with self-ensembled, deeply supervised 3D U-net neural networks: a BraTS 2020 challenge solution.</strong></a><br>\nCode (pytorch): <a href=\"https://github.com/lescientifik/open_brats2020\" target=\"_blank\">https://github.com/lescientifik/open_brats2020</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130410967-de4375f1-5328-4a16-a2a1-f7931e43c357.gif\" alt=\"resized_combined\"></p>",
      "rawMarkdown": "## Self-Ensembled (3D Test Time Augmentation)\n\nPaper: [**Brain tumor segmentation with self-ensembled, deeply supervised 3D U-net neural networks: a BraTS 2020 challenge solution.**](https://arxiv.org/pdf/2011.01045v2.pdf)\nCode (pytorch): https://github.com/lescientifik/open_brats2020\n\n![resized_combined](https://user-images.githubusercontent.com/17668390/130410967-de4375f1-5328-4a16-a2a1-f7931e43c357.gif)",
      "votes": null
    },
    {
      "id": "1486791",
      "postDate": "08/23/2021 08:10:50",
      "content": "<h2>Context-Aware Network</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2007.07788v3.pdf\" target=\"_blank\">CANet: Context-Aware Network for 3D Brain Glioma Segmentation</a><br>\nCode (pytorch): <a href=\"https://github.com/ZhihuaLiuEd/canetbrats\" target=\"_blank\">https://github.com/ZhihuaLiuEd/canetbrats</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130413209-216dca06-b428-4844-b171-ee800b97eb28.png\" alt=\"TransBTS\"></p>",
      "rawMarkdown": "## Context-Aware Network\n\nPaper: [CANet: Context-Aware Network for 3D Brain Glioma Segmentation](https://arxiv.org/pdf/2007.07788v3.pdf)\nCode (pytorch): https://github.com/ZhihuaLiuEd/canetbrats\n\n![TransBTS](https://user-images.githubusercontent.com/17668390/130413209-216dca06-b428-4844-b171-ee800b97eb28.png)",
      "votes": null
    },
    {
      "id": "1486794",
      "postDate": "08/23/2021 08:13:28",
      "content": "<h2>Knowledge Distillation</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2002.03688v1.pdf\" target=\"_blank\"><strong>Knowledge Distillation for Brain Tumor Segmentation</strong></a><br>\nCode: <a href=\"https://github.com/lachinov/brats2019\" target=\"_blank\">https://github.com/lachinov/brats2019</a></p>\n<hr>\n<h2>Weakly-Supervised Segmentation</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/1911.01738v2.pdf\" target=\"_blank\"><strong>Weakly Supervised Fine-Tuning Approach for Brain Tumor Segmentation Problem</strong></a><br>\nCode: <a href=\"https://github.com/segis95/BRATS_Segmentation\" target=\"_blank\">https://github.com/segis95/BRATS_Segmentation</a></p>\n<hr>\n<h2>Autofocus Layer for Semantic Segmentation</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/1805.08403v3.pdf\" target=\"_blank\"><strong>Autofocus Layer for Semantic Segmentation</strong></a><br>\nCode (pytorch): <a href=\"https://github.com/yaq007/Autofocus-Layer\" target=\"_blank\">https://github.com/yaq007/Autofocus-Layer</a><br>\nCode (tensorflow): <a href=\"https://github.com/perslev/Autofocus-Layer-TF\" target=\"_blank\">https://github.com/perslev/Autofocus-Layer-TF</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130414371-2b1f39cf-1cb0-48b8-85ef-0f7d836d8a18.png\" alt=\"TransBTS\"></p>",
      "rawMarkdown": "## Knowledge Distillation \n\nPaper: [**Knowledge Distillation for Brain Tumor Segmentation**](https://arxiv.org/pdf/2002.03688v1.pdf)\nCode: https://github.com/lachinov/brats2019\n\n---\n\n## Weakly-Supervised Segmentation \n\nPaper: [**Weakly Supervised Fine-Tuning Approach for Brain Tumor Segmentation Problem**](https://arxiv.org/pdf/1911.01738v2.pdf)\nCode: https://github.com/segis95/BRATS_Segmentation\n\n---\n\n## Autofocus Layer for Semantic Segmentation\n\nPaper: [**Autofocus Layer for Semantic Segmentation**](https://arxiv.org/pdf/1805.08403v3.pdf)\nCode (pytorch): https://github.com/yaq007/Autofocus-Layer\nCode (tensorflow): https://github.com/perslev/Autofocus-Layer-TF\n\n![TransBTS](https://user-images.githubusercontent.com/17668390/130414371-2b1f39cf-1cb0-48b8-85ef-0f7d836d8a18.png)",
      "votes": null
    },
    {
      "id": "1523584",
      "postDate": "09/25/2021 14:34:38",
      "content": "<h2>3D Swin Transformer</h2>\n<p>Code (pytorch): <a href=\"https://github.com/SwinTransformer/Video-Swin-Transformer\" target=\"_blank\">https://github.com/SwinTransformer/Video-Swin-Transformer</a><br>\n<img src=\"https://raw.githubusercontent.com/SwinTransformer/Video-Swin-Transformer/master/figures/teaser.png\" alt=\"\"></p>",
      "rawMarkdown": "## 3D Swin Transformer \nCode (pytorch): https://github.com/SwinTransformer/Video-Swin-Transformer\n![](https://raw.githubusercontent.com/SwinTransformer/Video-Swin-Transformer/master/figures/teaser.png)",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1486748,
      "author_name": "ipythonx",
      "author_url": "",
      "post_date": "08/23/2021 07:42:09",
      "content": "<h2>Transformer on BraTS</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2103.04430v2.pdf\" target=\"_blank\"><strong>TransBTS: Multimodal Brain Tumor Segmentation Using Transformer</strong></a><br>\nCode (pytorch): <a href=\"https://github.com/Wenxuan-1119/TransBTS\" target=\"_blank\">https://github.com/Wenxuan-1119/TransBTS</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130409377-167c3882-8a6c-498f-a2f3-c75624b70170.png\" alt=\"TransBTS\"></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1486758,
      "author_name": "ipythonx",
      "author_url": "",
      "post_date": "08/23/2021 07:48:46",
      "content": "<h2>Modeling with Missing Modalities</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2106.14591v2.pdf\" target=\"_blank\"><strong>ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities</strong></a><br>\nCode (pytorch): <a href=\"https://github.com/Wangyixinxin/ACN\" target=\"_blank\">https://github.com/Wangyixinxin/ACN</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130410273-91867cd8-9f3a-4707-ae7d-4ebae82fe17e.png\" alt=\"TransBTS\"></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1486769,
      "author_name": "ipythonx",
      "author_url": "",
      "post_date": "08/23/2021 07:55:45",
      "content": "<h2>Self-Ensembled (3D Test Time Augmentation)</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2011.01045v2.pdf\" target=\"_blank\"><strong>Brain tumor segmentation with self-ensembled, deeply supervised 3D U-net neural networks: a BraTS 2020 challenge solution.</strong></a><br>\nCode (pytorch): <a href=\"https://github.com/lescientifik/open_brats2020\" target=\"_blank\">https://github.com/lescientifik/open_brats2020</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130410967-de4375f1-5328-4a16-a2a1-f7931e43c357.gif\" alt=\"resized_combined\"></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1486791,
      "author_name": "ipythonx",
      "author_url": "",
      "post_date": "08/23/2021 08:10:50",
      "content": "<h2>Context-Aware Network</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2007.07788v3.pdf\" target=\"_blank\">CANet: Context-Aware Network for 3D Brain Glioma Segmentation</a><br>\nCode (pytorch): <a href=\"https://github.com/ZhihuaLiuEd/canetbrats\" target=\"_blank\">https://github.com/ZhihuaLiuEd/canetbrats</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130413209-216dca06-b428-4844-b171-ee800b97eb28.png\" alt=\"TransBTS\"></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1486794,
      "author_name": "ipythonx",
      "author_url": "",
      "post_date": "08/23/2021 08:13:28",
      "content": "<h2>Knowledge Distillation</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/2002.03688v1.pdf\" target=\"_blank\"><strong>Knowledge Distillation for Brain Tumor Segmentation</strong></a><br>\nCode: <a href=\"https://github.com/lachinov/brats2019\" target=\"_blank\">https://github.com/lachinov/brats2019</a></p>\n<hr>\n<h2>Weakly-Supervised Segmentation</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/1911.01738v2.pdf\" target=\"_blank\"><strong>Weakly Supervised Fine-Tuning Approach for Brain Tumor Segmentation Problem</strong></a><br>\nCode: <a href=\"https://github.com/segis95/BRATS_Segmentation\" target=\"_blank\">https://github.com/segis95/BRATS_Segmentation</a></p>\n<hr>\n<h2>Autofocus Layer for Semantic Segmentation</h2>\n<p>Paper: <a href=\"https://arxiv.org/pdf/1805.08403v3.pdf\" target=\"_blank\"><strong>Autofocus Layer for Semantic Segmentation</strong></a><br>\nCode (pytorch): <a href=\"https://github.com/yaq007/Autofocus-Layer\" target=\"_blank\">https://github.com/yaq007/Autofocus-Layer</a><br>\nCode (tensorflow): <a href=\"https://github.com/perslev/Autofocus-Layer-TF\" target=\"_blank\">https://github.com/perslev/Autofocus-Layer-TF</a></p>\n<p><img src=\"https://user-images.githubusercontent.com/17668390/130414371-2b1f39cf-1cb0-48b8-85ef-0f7d836d8a18.png\" alt=\"TransBTS\"></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1523584,
      "author_name": "ipythonx",
      "author_url": "",
      "post_date": "09/25/2021 14:34:38",
      "content": "<h2>3D Swin Transformer</h2>\n<p>Code (pytorch): <a href=\"https://github.com/SwinTransformer/Video-Swin-Transformer\" target=\"_blank\">https://github.com/SwinTransformer/Video-Swin-Transformer</a><br>\n<img src=\"https://raw.githubusercontent.com/SwinTransformer/Video-Swin-Transformer/master/figures/teaser.png\" alt=\"\"></p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1472404": "Interesting work \n\npaper: [Multi-Modal MRI Reconstruction with Spatial Alignment Network](https://arxiv.org/pdf/2108.05603v1.pdf)\ncode (pytorch): https://github.com/woxuankai/spatialalignmentnetwork\n\n![Screenshot 2021-08-15 024301](https://user-images.githubusercontent.com/17668390/129459567-903797f7-86f3-4ee8-9b37-fb98ec93b8a5.png)",
    "1486748": "## Transformer on BraTS\n\nPaper: [**TransBTS: Multimodal Brain Tumor Segmentation Using Transformer**](https://arxiv.org/pdf/2103.04430v2.pdf)\nCode (pytorch): https://github.com/Wenxuan-1119/TransBTS\n\n![TransBTS](https://user-images.githubusercontent.com/17668390/130409377-167c3882-8a6c-498f-a2f3-c75624b70170.png)",
    "1486758": "## Modeling with Missing Modalities\n\nPaper: [**ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities**](https://arxiv.org/pdf/2106.14591v2.pdf)\nCode (pytorch): https://github.com/Wangyixinxin/ACN\n\n![TransBTS](https://user-images.githubusercontent.com/17668390/130410273-91867cd8-9f3a-4707-ae7d-4ebae82fe17e.png)",
    "1486769": "## Self-Ensembled (3D Test Time Augmentation)\n\nPaper: [**Brain tumor segmentation with self-ensembled, deeply supervised 3D U-net neural networks: a BraTS 2020 challenge solution.**](https://arxiv.org/pdf/2011.01045v2.pdf)\nCode (pytorch): https://github.com/lescientifik/open_brats2020\n\n![resized_combined](https://user-images.githubusercontent.com/17668390/130410967-de4375f1-5328-4a16-a2a1-f7931e43c357.gif)",
    "1486791": "## Context-Aware Network\n\nPaper: [CANet: Context-Aware Network for 3D Brain Glioma Segmentation](https://arxiv.org/pdf/2007.07788v3.pdf)\nCode (pytorch): https://github.com/ZhihuaLiuEd/canetbrats\n\n![TransBTS](https://user-images.githubusercontent.com/17668390/130413209-216dca06-b428-4844-b171-ee800b97eb28.png)",
    "1486794": "## Knowledge Distillation \n\nPaper: [**Knowledge Distillation for Brain Tumor Segmentation**](https://arxiv.org/pdf/2002.03688v1.pdf)\nCode: https://github.com/lachinov/brats2019\n\n---\n\n## Weakly-Supervised Segmentation \n\nPaper: [**Weakly Supervised Fine-Tuning Approach for Brain Tumor Segmentation Problem**](https://arxiv.org/pdf/1911.01738v2.pdf)\nCode: https://github.com/segis95/BRATS_Segmentation\n\n---\n\n## Autofocus Layer for Semantic Segmentation\n\nPaper: [**Autofocus Layer for Semantic Segmentation**](https://arxiv.org/pdf/1805.08403v3.pdf)\nCode (pytorch): https://github.com/yaq007/Autofocus-Layer\nCode (tensorflow): https://github.com/perslev/Autofocus-Layer-TF\n\n![TransBTS](https://user-images.githubusercontent.com/17668390/130414371-2b1f39cf-1cb0-48b8-85ef-0f7d836d8a18.png)",
    "1523584": "## 3D Swin Transformer \nCode (pytorch): https://github.com/SwinTransformer/Video-Swin-Transformer\n![](https://raw.githubusercontent.com/SwinTransformer/Video-Swin-Transformer/master/figures/teaser.png)"
  },
  "source": "meta"
}