{ "id": 256199, "title": "Understanding 3D image classification ", "url": "/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/256199", "author_name": "", "post_date": "2021-07-31T09:47:55.788786Z", "votes": 32, "comment_count": 5, "views": 0, "content": "

Hello all,

\n

I'm newbie about 3D image classification and would like to deepen my understanding through this competition.

\n

I guess there are similar competitors like me, so I'd like to share some knowledge with them.
\nI create this topic to track and share my work, please make use this as you need.

\n\n

I'll update further findings later:)

", "messages": [ { "id": "1405896", "postDate": "07/31/2021 09:47:55", "content": "

Hello all,

\n

I'm newbie about 3D image classification and would like to deepen my understanding through this competition.

\n

I guess there are similar competitors like me, so I'd like to share some knowledge with them.
\nI create this topic to track and share my work, please make use this as you need.

\n\n

I'll update further findings later:)

", "rawMarkdown": "Hello all, \n\nI'm newbie about `3D image classification` and would like to deepen my understanding through this competition. \n\nI guess there are similar competitors like me, so I'd like to share some knowledge with them. \nI create this topic to track and share my work, please make use this as you need. \n\n* [(Link)](https://keras.io/examples/vision/3D_image_classification/) **Model training of 3D image classification example by Keras** \n -> In this page, you can see the model training of 3D image classification with simple code. \nSome related papers can be also referred. \n\n* [(Link)](https://arxiv.org/pdf/2007.13224.pdf) **An experiment about `Uniformizing Techniques` for 3D preprocessing with Git implementation** \n -> It deals with how to resize the dims of 3D data like `CT scan`. \n\n* [(Link)](https://towardsdatascience.com/explicit-auc-maximization-70beef6db14e) **A loss function for optimizing AUC** \n -> This article introduces a custom loss function for `AUC` optimization. \n\n\nI'll update further findings later:)", "votes": null }, { "id": "1408054", "postDate": "08/02/2021 09:20:44", "content": "

Hi,
\nthis might be a nice place to start as well:
\nhttps://arxiv.org/pdf/2004.00218.pdf

", "rawMarkdown": "Hi,\nthis might be a nice place to start as well:\nhttps://arxiv.org/pdf/2004.00218.pdf", "votes": null }, { "id": "1408287", "postDate": "08/02/2021 12:01:38", "content": "

Hi @charzu ,
\nThank you for sharing! I will look into it:)

\n

I also would like to share my findings about Uniformizing Techniques for 3D preprocessing here.
\nThis paper shows some experiments about 3D CT scan image processing!

", "rawMarkdown": "Hi @charzu , \nThank you for sharing! I will look into it:) \n\nI also would like to share my findings about `Uniformizing Techniques` for 3D preprocessing [here](https://arxiv.org/pdf/2007.13224.pdf). \nThis paper shows some experiments about 3D CT scan image processing!", "votes": null }, { "id": "1453234", "postDate": "08/05/2021 19:55:19", "content": "

Thanks for sharing this!

", "rawMarkdown": "Thanks for sharing this!", "votes": null }, { "id": "1469175", "postDate": "08/12/2021 18:46:36", "content": "

Thanks for sharing !

", "rawMarkdown": "Thanks for sharing !", "votes": null }, { "id": "1813365", "postDate": "06/06/2022 18:51:55", "content": "

Thanks for sharing, good insight!!

", "rawMarkdown": "Thanks for sharing, good insight!!", "votes": null } ], "comments": [ { "id": 1408054, "author_name": "charzu", "author_url": "", "post_date": "08/02/2021 09:20:44", "content": "

Hi,
\nthis might be a nice place to start as well:
\nhttps://arxiv.org/pdf/2004.00218.pdf

", "votes": null, "replies": [ { "id": 1408287, "author_name": "narikawa", "author_url": "", "post_date": "08/02/2021 12:01:38", "content": "

Hi @charzu ,
\nThank you for sharing! I will look into it:)

\n

I also would like to share my findings about Uniformizing Techniques for 3D preprocessing here.
\nThis paper shows some experiments about 3D CT scan image processing!

", "votes": null, "replies": [] } ] }, { "id": 1453234, "author_name": "hsudhakaran", "author_url": "", "post_date": "08/05/2021 19:55:19", "content": "

Thanks for sharing this!

", "votes": null, "replies": [] }, { "id": 1469175, "author_name": "cinthiakleiner", "author_url": "", "post_date": "08/12/2021 18:46:36", "content": "

Thanks for sharing !

", "votes": null, "replies": [] }, { "id": 1813365, "author_name": "deepak007chaubey", "author_url": "", "post_date": "06/06/2022 18:51:55", "content": "

Thanks for sharing, good insight!!

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1405896": "Hello all, \n\nI'm newbie about `3D image classification` and would like to deepen my understanding through this competition. \n\nI guess there are similar competitors like me, so I'd like to share some knowledge with them. \nI create this topic to track and share my work, please make use this as you need. \n\n* [(Link)](https://keras.io/examples/vision/3D_image_classification/) **Model training of 3D image classification example by Keras** \n -> In this page, you can see the model training of 3D image classification with simple code. \nSome related papers can be also referred. \n\n* [(Link)](https://arxiv.org/pdf/2007.13224.pdf) **An experiment about `Uniformizing Techniques` for 3D preprocessing with Git implementation** \n -> It deals with how to resize the dims of 3D data like `CT scan`. \n\n* [(Link)](https://towardsdatascience.com/explicit-auc-maximization-70beef6db14e) **A loss function for optimizing AUC** \n -> This article introduces a custom loss function for `AUC` optimization. \n\n\nI'll update further findings later:)", "1408054": "Hi,\nthis might be a nice place to start as well:\nhttps://arxiv.org/pdf/2004.00218.pdf", "1408287": "Hi @charzu , \nThank you for sharing! I will look into it:) \n\nI also would like to share my findings about `Uniformizing Techniques` for 3D preprocessing [here](https://arxiv.org/pdf/2007.13224.pdf). \nThis paper shows some experiments about 3D CT scan image processing!", "1453234": "Thanks for sharing this!", "1469175": "Thanks for sharing !", "1813365": "Thanks for sharing, good insight!!" }, "source": "meta" }