Convert issues to project pages, yay!

content/project/project_17.md

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+{
+  "Title": "MRI based brain thermometry",
+  "link_to_issue": "https://github.com/brainhackorg/global2024/issues/17",
+  "issue_number": 17,
+  "labels": [
+    {
+      "name": "git_skills:0_none",
+      "description": "",
+      "color": "5B6C2C"
+    },
+    {
+      "name": "hub:melbourne_aus",
+      "description": "",
+      "color": "0E8A16"
+    },
+    {
+      "name": "modality:DWI",
+      "description": "",
+      "color": "1d76db"
+    },
+    {
+      "name": "modality:MRI",
+      "description": "",
+      "color": "1d76db"
+    },
+    {
+      "name": "programming:documentation",
+      "description": "",
+      "color": "5319E7"
+    },
+    {
+      "name": "programming:Python",
+      "description": "",
+      "color": "5319E7"
+    },
+    {
+      "name": "project",
+      "description": "",
+      "color": "B60205"
+    },
+    {
+      "name": "project_development_status:0_concept_no_content",
+      "description": "",
+      "color": "D93F0B"
+    },
+    {
+      "name": "project_type:coding_methods",
+      "description": null,
+      "color": "ededed"
+    },
+    {
+      "name": "project_type:data_management",
+      "description": null,
+      "color": "ededed"
+    },
+    {
+      "name": "project_type:documentation",
+      "description": null,
+      "color": "ededed"
+    },
+    {
+      "name": "project_type:method_development",
+      "description": null,
+      "color": "ededed"
+    },
+    {
+      "name": "project_type:pipeline_development",
+      "description": null,
+      "color": "ededed"
+    },
+    {
+      "name": "status:web_ready",
+      "description": "",
+      "color": "0E8A16"
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+    {
+      "name": "tools:Brainstorm",
+      "description": "",
+      "color": "EA1D4E"
+    },
+    {
+      "name": "topic:deep_learning",
+      "description": "",
+      "color": "FBCA04"
+    },
+    {
+      "name": "topic:MR_methodologies",
+      "description": "",
+      "color": "FBCA04"
+    },
+    {
+      "name": "topic:statistical_modelling",
+      "description": "",
+      "color": "FBCA04"
+    },
+    {
+      "name": "topic:diffusion",
+      "description": null,
+      "color": "ededed"
+    }
+  ],
+  "content": "### Title\n\nMRI brain thermometry\n\n### Leaders\n\nChristian Behler (@ChristianBehler), Anna Behler (@Anna_Neurosci)\n\n### Collaborators\n\n_No response_\n\n### Brainhack Global 2024 Event\n\nBrainhack Aus\n\n### Project Description\n\nThe brain is hot and its thermoregulation underlies different boundary conditions than the body's thermoregulation. Heat in the brain is produced as by-product of metabolism and gets primarily removed by blood flow. In the presence of tumours or neurodegenerative processes this balance can be disturbed. \r\nMRI can be used to measure brain temperature via spectroscopy or diffusion. The existing analysis pipelines face many problems. That's what this project is going to address. The first aim is to build a model for the calibration of MRS, and test it on real data. Developing code to handle MRS files is also on the to do list. Secondly, we'd like improve the thermometry based on DWI by automated segmentation of the fourth ventricle. It's also planned to explore how machine learning could be used to remove diffusion artefacts. \n\n### Link to project repository/sources\n\nhttps://github.com/AnnaBhlr/MRI_BrainThermometry\n\n### Goals for Brainhack Global\n\n- Model for MRS calibration \r\n- Code/pipeline to handle MRS files\r\n- Automated segmentation of 4th ventricle on diffusion data\r\n- Ideas brainstormed on diffusion artefact removal\n\n### Good first issues\n\n- Could GLMM a good path for model of MRS calibration?\r\n- Which open source data sets could be used to implement automated segmentation? \n\n### Communication channels\n\nhttps://mattermost.brainhack.org/brainhack/channels/brainthermometry\n\n### Skills\n\nNewcomer to deep learning pro...each project aim fits a different skill level.\n\n### Onboarding documentation\n\n_No response_\n\n### What will participants learn?\n\nParticipants would learn about an overlooked topic and methodology. Coding newbie can start easy with computational modelling and how to handle imaging data.\n\n### Data to use\n\n_No response_\n\n### Number of collaborators\n\nmore\n\n### Credit to collaborators\n\nProject contributors will be acknowledged on project readme and will be listed as co-authors if project eventually ends in a publication.\n\n### Image\n\n<img width=\"65\" alt=\"Picture 1\" src=\"https://github.com/user-attachments/assets/095a6a8b-66b0-45c7-ace2-69015ca93022\">\r\n\n\n### Type\n\ncoding_methods, data_management, method_development, pipeline_development\n\n### Development status\n\n0_concept_no_content\n\n### Topic\n\ndeep_learning, diffusion, MR_methodologies, statistical_modelling, other\n\n### Tools\n\nBrainstorm, other\n\n### Programming language\n\nPython\n\n### Modalities\n\nDWI, other\n\n### Git skills\n\n0_no_git_skills\n\n### Anything else?\n\n_No response_\n\n### Things to do after the project is submitted and ready to review.\n\n- [X] Add a comment below the main post of your issue saying: `Hi @brainhackorg/project-monitors my project is ready!`\n- [ ] Twitter-sized summary of your project pitch.",
+  "project_url": "https://github.com/AnnaBhlr/MRI_BrainThermometry",
+  "project_description": "\n\nThe brain is hot and its thermoregulation underlies different boundary conditions than the body's thermoregulation. Heat in the brain is produced as by-product of metabolism and gets primarily removed by blood flow. In the presence of tumours or neurodegenerative processes this balance can be disturbed. \r\nMRI can be used to measure brain temperature via spectroscopy or diffusion. The existing analysis pipelines face many problems. That's what this project is going to address. The first aim is to build a model for the calibration of MRS, and test it on real data. Developing code to handle MRS files is also on the to do list. Secondly, we'd like improve the thermometry based on DWI by automated segmentation of the fourth ventricle. It's also planned to explore how machine learning could be used to remove diffusion artefacts. \n\n"
+}