{ "id": 453879, "title": "🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚", "url": "/competitions/blood-vessel-segmentation/discussion/453879", "author_name": "", "post_date": "2023-11-08T05:00:20.729420200Z", "votes": 12, "comment_count": 2, "views": 0, "content": "

## 🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚

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Following are some wonderful resources from Kaggle itself

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\"Resources

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Full Preprocessing Tutorial from Data Science Bowl 2017

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It covers Loading the DICOM files, Resampling to an isomorphic resolution, 3D plotting, segmentation and Normalization along with Zero centerin the scans.

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Candidate Generation and LUNA16 preprocessing

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Another version of the above notebook from the DS Bowl in 2017 Loading the DICOM files, Resampling to an isomorphic resolution, 3D plotting, segmentation and Normalization along with Zero centerin the scans.

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Pulmonary Dicom Preprocessing

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Another version of the above notebook from the DS Bowl in 2017 pulmonary competitions based on CT scans

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Vesuvius Challenge: Ink Detection tutorial

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This is from another competition - Vesuvius Challenge - Ink Detection

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First pass through Data w/ 3D ConvNet

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Another rendering of the DS Bowl 2017_

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Exploratory Data Analysis

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Another nice EDA rendering of the DS Bowl 2017_

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3D MRI Brain tumor segmentation || U-NET

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_ Wonderful rendering of Segmentation of gliomas in pre-operative MRI scans._

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🦴 RSNA Fracture Detection - in-depth EDA

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From another competition RSNA 2022 Cervical Spine Fracture Detection - Nice read

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3D Solution with MONAI [Infer]

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From another competition UW-Madison GI Tract Image Segmentation - Nice read

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Hope you like the content.

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Best wishes for the competition

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\"SenNet

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🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚

", "messages": [ { "id": "2516936", "postDate": "11/08/2023 05:00:20", "content": "

## 🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚

\n

Following are some wonderful resources from Kaggle itself

\n

\"Resources

\n

Full Preprocessing Tutorial from Data Science Bowl 2017

\n
\n
\n
\n

It covers Loading the DICOM files, Resampling to an isomorphic resolution, 3D plotting, segmentation and Normalization along with Zero centerin the scans.

\n
\n
\n
\n

Candidate Generation and LUNA16 preprocessing

\n
\n
\n
\n

Another version of the above notebook from the DS Bowl in 2017 Loading the DICOM files, Resampling to an isomorphic resolution, 3D plotting, segmentation and Normalization along with Zero centerin the scans.

\n
\n
\n
\n

Pulmonary Dicom Preprocessing

\n
\n
\n
\n

Another version of the above notebook from the DS Bowl in 2017 pulmonary competitions based on CT scans

\n
\n
\n
\n

Vesuvius Challenge: Ink Detection tutorial

\n
\n
\n
\n

This is from another competition - Vesuvius Challenge - Ink Detection

\n
\n
\n
\n

First pass through Data w/ 3D ConvNet

\n
\n
\n
\n

Another rendering of the DS Bowl 2017_

\n
\n
\n
\n

Exploratory Data Analysis

\n
\n
\n
\n

Another nice EDA rendering of the DS Bowl 2017_

\n
\n
\n
\n

3D MRI Brain tumor segmentation || U-NET

\n
\n
\n
\n

_ Wonderful rendering of Segmentation of gliomas in pre-operative MRI scans._

\n
\n
\n
\n

🦴 RSNA Fracture Detection - in-depth EDA

\n
\n
\n
\n

From another competition RSNA 2022 Cervical Spine Fracture Detection - Nice read

\n
\n
\n
\n

3D Solution with MONAI [Infer]

\n
\n
\n
\n

From another competition UW-Madison GI Tract Image Segmentation - Nice read

\n
\n
\n
\n

Hope you like the content.

\n
\n

Best wishes for the competition

\n

\"SenNet

\n

🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚

", "rawMarkdown": "# ## 🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚\n\n## Following are some wonderful resources from Kaggle itself\n\n![Resources for 3D visualization ](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4432707%2Fe4830f808bca152da260521909b298e6%2FKaggle_3D_.PNG?generation=1699418912408849&alt=media)\n\n## [Full Preprocessing Tutorial from Data Science Bowl 2017](https://www.kaggle.com/code/gzuidhof/full-preprocessing-tutorial)\n>>> It covers _Loading the DICOM files, Resampling to an isomorphic resolution, 3D plotting, segmentation and Normalization along with Zero centerin the scans._\n\n## [Candidate Generation and LUNA16 preprocessing](https://www.kaggle.com/code/arnavkj95/candidate-generation-and-luna16-preprocessing)\n>>> Another version of the above notebook from the DS Bowl in 2017 _Loading the DICOM files, Resampling to an isomorphic resolution, 3D plotting, segmentation and Normalization along with Zero centerin the scans._\n\n## [Pulmonary Dicom Preprocessing](https://www.kaggle.com/code/arnavkj95/candidate-generation-and-luna16-preprocessing)\n>>> Another version of the above notebook from the DS Bowl in 2017 _pulmonary competitions based on CT scans_\n\n## [Vesuvius Challenge: Ink Detection tutorial](https://www.kaggle.com/code/jpposma/vesuvius-challenge-ink-detection-tutorial)\n>>> This is from another competition - [Vesuvius Challenge - Ink Detection ](https://www.kaggle.com/competitions/vesuvius-challenge-ink-detection)\n\n## [First pass through Data w/ 3D ConvNet](https://www.kaggle.com/code/sentdex/first-pass-through-data-w-3d-convnet)\n>>>_Another rendering of the DS Bowl 2017__\n\n##[Exploratory Data Analysis](https://www.kaggle.com/code/anokas/exploratory-data-analysis-4)\n>>>_Another nice EDA rendering of the DS Bowl 2017__\n\n##[3D MRI Brain tumor segmentation || U-NET](https://www.kaggle.com/code/rastislav/3d-mri-brain-tumor-segmentation-u-net)\n>>>_ Wonderful rendering of Segmentation of gliomas in pre-operative MRI scans._\n\n##[🦴 RSNA Fracture Detection - in-depth EDA](https://www.kaggle.com/code/samuelcortinhas/rsna-fracture-detection-in-depth-eda)\n>>>_From another competition [RSNA 2022 Cervical Spine Fracture Detection](https://www.kaggle.com/datasets/samuelcortinhas/rsna-2022-spine-fracture-detection-metadata) - Nice read_\n\n##[3D Solution with MONAI [Infer]](https://www.kaggle.com/code/yiheng/3d-solution-with-monai-infer)\n>>>_From another competition [UW-Madison GI Tract Image Segmentation](https://www.kaggle.com/competitions/uw-madison-gi-tract-image-segmentation) - Nice read_\n\nHope you like the content. \n\n_________________\n### Best wishes for the competition \n[![SenNet + HOA - Hacking the Human Vasculature in 3D](https://i.postimg.cc/d0kx62Ys/360-F-238882142-RR07-WHn-FIm82-FA6x-Rv-U7-MLos0-Mxrf-Hgw.jpg)](https://postimg.cc/jWTcdJ2m)\n\n\n## 🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚", "votes": null }, { "id": "2532423", "postDate": "11/21/2023 04:18:15", "content": "

Your comments are welcome!

", "rawMarkdown": "Your comments are welcome!", "votes": null }, { "id": "2557703", "postDate": "12/11/2023 16:14:10", "content": "

Great work on summarising. Developed a 3D patch based UNET model that runs on TPU. I thought it will be a easy quickstart:

\n

https://www.kaggle.com/code/dhinkris/training-patch-based-3d-unet-tf-tpu

", "rawMarkdown": "Great work on summarising. Developed a 3D patch based UNET model that runs on TPU. I thought it will be a easy quickstart: \n\nhttps://www.kaggle.com/code/dhinkris/training-patch-based-3d-unet-tf-tpu", "votes": null } ], "comments": [ { "id": 2532423, "author_name": "kalilurrahman", "author_url": "", "post_date": "11/21/2023 04:18:15", "content": "

Your comments are welcome!

", "votes": null, "replies": [] }, { "id": 2557703, "author_name": "dhinkris", "author_url": "", "post_date": "12/11/2023 16:14:10", "content": "

Great work on summarising. Developed a 3D patch based UNET model that runs on TPU. I thought it will be a easy quickstart:

\n

https://www.kaggle.com/code/dhinkris/training-patch-based-3d-unet-tf-tpu

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "2516936": "# ## 🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚\n\n## Following are some wonderful resources from Kaggle itself\n\n![Resources for 3D visualization ](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4432707%2Fe4830f808bca152da260521909b298e6%2FKaggle_3D_.PNG?generation=1699418912408849&alt=media)\n\n## [Full Preprocessing Tutorial from Data Science Bowl 2017](https://www.kaggle.com/code/gzuidhof/full-preprocessing-tutorial)\n>>> It covers _Loading the DICOM files, Resampling to an isomorphic resolution, 3D plotting, segmentation and Normalization along with Zero centerin the scans._\n\n## [Candidate Generation and LUNA16 preprocessing](https://www.kaggle.com/code/arnavkj95/candidate-generation-and-luna16-preprocessing)\n>>> Another version of the above notebook from the DS Bowl in 2017 _Loading the DICOM files, Resampling to an isomorphic resolution, 3D plotting, segmentation and Normalization along with Zero centerin the scans._\n\n## [Pulmonary Dicom Preprocessing](https://www.kaggle.com/code/arnavkj95/candidate-generation-and-luna16-preprocessing)\n>>> Another version of the above notebook from the DS Bowl in 2017 _pulmonary competitions based on CT scans_\n\n## [Vesuvius Challenge: Ink Detection tutorial](https://www.kaggle.com/code/jpposma/vesuvius-challenge-ink-detection-tutorial)\n>>> This is from another competition - [Vesuvius Challenge - Ink Detection ](https://www.kaggle.com/competitions/vesuvius-challenge-ink-detection)\n\n## [First pass through Data w/ 3D ConvNet](https://www.kaggle.com/code/sentdex/first-pass-through-data-w-3d-convnet)\n>>>_Another rendering of the DS Bowl 2017__\n\n##[Exploratory Data Analysis](https://www.kaggle.com/code/anokas/exploratory-data-analysis-4)\n>>>_Another nice EDA rendering of the DS Bowl 2017__\n\n##[3D MRI Brain tumor segmentation || U-NET](https://www.kaggle.com/code/rastislav/3d-mri-brain-tumor-segmentation-u-net)\n>>>_ Wonderful rendering of Segmentation of gliomas in pre-operative MRI scans._\n\n##[🦴 RSNA Fracture Detection - in-depth EDA](https://www.kaggle.com/code/samuelcortinhas/rsna-fracture-detection-in-depth-eda)\n>>>_From another competition [RSNA 2022 Cervical Spine Fracture Detection](https://www.kaggle.com/datasets/samuelcortinhas/rsna-2022-spine-fracture-detection-metadata) - Nice read_\n\n##[3D Solution with MONAI [Infer]](https://www.kaggle.com/code/yiheng/3d-solution-with-monai-infer)\n>>>_From another competition [UW-Madison GI Tract Image Segmentation](https://www.kaggle.com/competitions/uw-madison-gi-tract-image-segmentation) - Nice read_\n\nHope you like the content. \n\n_________________\n### Best wishes for the competition \n[![SenNet + HOA - Hacking the Human Vasculature in 3D](https://i.postimg.cc/d0kx62Ys/360-F-238882142-RR07-WHn-FIm82-FA6x-Rv-U7-MLos0-Mxrf-Hgw.jpg)](https://postimg.cc/jWTcdJ2m)\n\n\n## 🔮💥🤖Nice Resources for 3D Visualization - Kaggle Notebooks🔥🏆📚", "2532423": "Your comments are welcome!", "2557703": "Great work on summarising. Developed a 3D patch based UNET model that runs on TPU. I thought it will be a easy quickstart: \n\nhttps://www.kaggle.com/code/dhinkris/training-patch-based-3d-unet-tf-tpu" }, "source": "meta" }