Modifications
On 12 décembre 2023 à 20:06:37 +0800,
以柔 紀:
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Renamed resource MRI Cortical Thickness Image Dataset - Schizophrenia to MRI Freesurfer Dataset - Schizophrenia in Taiwan Aging and Mental Illness Cohort
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Set format of resource MRI Freesurfer Dataset - Schizophrenia to mgz (previously NIFTI) in Taiwan Aging and Mental Illness Cohort
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Updated description of resource MRI Freesurfer Dataset - Schizophrenia in Taiwan Aging and Mental Illness Cohort from
This dataset comprises preprocessed MRI images acquired from schizophrenia patients. These images have been processed using FSL to generate data on cortical thickness.
toThis dataset comprises preprocessed MRI images acquired from schizophrenia patients. These images have been processed using Freesurfer to generate data on brain structural features.
| f | 1 | { | f | 1 | { |
| 2 | "author": "Albert C. Yang, MD", | 2 | "author": "Albert C. Yang, MD", | ||
| 3 | "author_email": "accyang@nycu.edu.tw", | 3 | "author_email": "accyang@nycu.edu.tw", | ||
| 4 | "creator_user_id": "1d214521-cf55-43ab-8a2a-1d7307cf05e7", | 4 | "creator_user_id": "1d214521-cf55-43ab-8a2a-1d7307cf05e7", | ||
| 5 | "extras": [], | 5 | "extras": [], | ||
| n | 6 | "groups": [], | n | 6 | "groups": [ |
| 7 | { | ||||
| 8 | "description": "", | ||||
| 9 | "display_name": "Brain Image", | ||||
| 10 | "id": "9765d9ee-aa92-4df1-a4e8-449093b96e9d", | ||||
| 11 | "image_display_url": | ||||
| 12 | ps://data.dmc.nycu.edu.tw/uploads/group/2022-05-20-061942.864108.png", | ||||
| 13 | "name": "brain-image", | ||||
| 14 | "title": "Brain Image" | ||||
| 15 | } | ||||
| 16 | ], | ||||
| 7 | "id": "804e1201-067d-4c50-ae36-f549b714a38a", | 17 | "id": "804e1201-067d-4c50-ae36-f549b714a38a", | ||
| 8 | "isopen": true, | 18 | "isopen": true, | ||
| 9 | "license_id": "cc-by", | 19 | "license_id": "cc-by", | ||
| 10 | "license_title": "Creative Commons Attribution", | 20 | "license_title": "Creative Commons Attribution", | ||
| 11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 21 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
| 12 | "maintainer": "I-Jou Chi", | 22 | "maintainer": "I-Jou Chi", | ||
| 13 | "maintainer_email": "irene159irene159.md10@nycu.edu.tw", | 23 | "maintainer_email": "irene159irene159.md10@nycu.edu.tw", | ||
| 14 | "metadata_created": "2023-12-06T01:48:03.763872", | 24 | "metadata_created": "2023-12-06T01:48:03.763872", | ||
| n | 15 | "metadata_modified": "2023-12-12T08:15:54.197051", | n | 25 | "metadata_modified": "2023-12-12T12:06:37.776461", |
| 16 | "name": "taiwan-aging-and-mental-illness-cohort-tami", | 26 | "name": "taiwan-aging-and-mental-illness-cohort-tami", | ||
| 17 | "notes": "##Overview##\r\n\r\nThe Taiwan Aging and Mental Illness | 27 | "notes": "##Overview##\r\n\r\nThe Taiwan Aging and Mental Illness | ||
| 18 | Cohort (TAMI) presents a detailed and extensive Magnetic Resonance | 28 | Cohort (TAMI) presents a detailed and extensive Magnetic Resonance | ||
| 19 | Imaging (MRI) study dataset, spearheaded by Professor Albert C. Yang. | 29 | Imaging (MRI) study dataset, spearheaded by Professor Albert C. Yang. | ||
| 20 | This project, initiated in 2012, is a collaboration between Taipei | 30 | This project, initiated in 2012, is a collaboration between Taipei | ||
| 21 | Veterans General Hospital and National Yang Ming Chiao Tung | 31 | Veterans General Hospital and National Yang Ming Chiao Tung | ||
| 22 | University, Yang Ming campus. It focuses on providing valuable | 32 | University, Yang Ming campus. It focuses on providing valuable | ||
| 23 | insights into various mental illnesses and their impact on brain | 33 | insights into various mental illnesses and their impact on brain | ||
| 24 | structure and function.\r\n\r\n##Dataset | 34 | structure and function.\r\n\r\n##Dataset | ||
| 25 | Composition##\r\n\r\n__Participants__: The study includes 1,265 | 35 | Composition##\r\n\r\n__Participants__: The study includes 1,265 | ||
| 26 | participants, encompassing 587 healthy individuals and 678 patients | 36 | participants, encompassing 587 healthy individuals and 678 patients | ||
| 27 | diagnosed with mental illnesses such as schizophrenia, bipolar | 37 | diagnosed with mental illnesses such as schizophrenia, bipolar | ||
| 28 | disorder, and depression.\r\n\r\n__Imaging Data__: Participants have | 38 | disorder, and depression.\r\n\r\n__Imaging Data__: Participants have | ||
| 29 | undergone comprehensive brain imaging scans at the MRI facility | 39 | undergone comprehensive brain imaging scans at the MRI facility | ||
| 30 | located at the Yang Ming campus.\r\n\r\n__Types of MRI | 40 | located at the Yang Ming campus.\r\n\r\n__Types of MRI | ||
| 31 | Data__:\r\n\r\n__Structural MRI__: Includes data from Structural and | 41 | Data__:\r\n\r\n__Structural MRI__: Includes data from Structural and | ||
| 32 | Diffusion Tensor Imaging.\r\n\r\n__Functional MRI__: Provides data on | 42 | Diffusion Tensor Imaging.\r\n\r\n__Functional MRI__: Provides data on | ||
| 33 | brain activity and function.\r\n\r\n##Dataset Scope and | 43 | brain activity and function.\r\n\r\n##Dataset Scope and | ||
| 34 | Objectives##\r\n\r\nTo understand the neurological impacts of aging | 44 | Objectives##\r\n\r\nTo understand the neurological impacts of aging | ||
| 35 | and mental illnesses.\r\n\r\nTo explore the structural and functional | 45 | and mental illnesses.\r\n\r\nTo explore the structural and functional | ||
| 36 | brain changes associated with schizophrenia, bipolar disorder, and | 46 | brain changes associated with schizophrenia, bipolar disorder, and | ||
| 37 | depression.\r\nAdditional Data:\r\n\r\nAlong with the MRI scans, the | 47 | depression.\r\nAdditional Data:\r\n\r\nAlong with the MRI scans, the | ||
| 38 | dataset also contains:\r\n\r\nDemographic information of | 48 | dataset also contains:\r\n\r\nDemographic information of | ||
| 39 | participants.\r\nDetailed clinical data for each | 49 | participants.\r\nDetailed clinical data for each | ||
| 40 | participant.\r\n\r\n##Citation Guidelines for Using the TAMI | 50 | participant.\r\n\r\n##Citation Guidelines for Using the TAMI | ||
| 41 | Dataset##\r\n\r\nWhen utilizing data from the TAMI in your research, | 51 | Dataset##\r\n\r\nWhen utilizing data from the TAMI in your research, | ||
| 42 | please cite the following paper in your published | 52 | please cite the following paper in your published | ||
| 43 | nhttps://www.sciencedirect.com/science/article/pii/S019745801200276X", | 53 | nhttps://www.sciencedirect.com/science/article/pii/S019745801200276X", | ||
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| 45 | "num_tags": 6, | 55 | "num_tags": 6, | ||
| 46 | "organization": { | 56 | "organization": { | ||
| 47 | "approval_status": "approved", | 57 | "approval_status": "approved", | ||
| 48 | "created": "2022-05-20T11:47:43.716226", | 58 | "created": "2022-05-20T11:47:43.716226", | ||
| n | 49 | "description": "", | n | 59 | "description": "National Yang Ming Chiao Tung University (NYCU; |
| 60 | Chinese: \u570b\u7acb\u967d\u660e\u4ea4\u901a\u5927\u5b78) is a public | ||||
| 61 | research university in Taipei and Hsinchu, Taiwan. It was created in | ||||
| 62 | 2021 through the merger of National Yang-Ming University and National | ||||
| 63 | Chiao Tung University. At present, there are 19 colleges, 74 | ||||
| 64 | university/college level research centers, and 1 hospital in Yilan.", | ||||
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| 53 | "name": "national-yang-ming-chiao-tung-university", | 68 | "name": "national-yang-ming-chiao-tung-university", | ||
| 54 | "state": "active", | 69 | "state": "active", | ||
| 55 | "title": "National Yang Ming Chiao Tung University", | 70 | "title": "National Yang Ming Chiao Tung University", | ||
| 56 | "type": "organization" | 71 | "type": "organization" | ||
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| 219 | "last_modified": "2023-12-06T02:23:20.843647", | 234 | "last_modified": "2023-12-06T02:23:20.843647", | ||
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| 223 | "name": "Schizophrenia_subcortical_volume.csv", | 238 | "name": "Schizophrenia_subcortical_volume.csv", | ||
| 224 | "package_id": "804e1201-067d-4c50-ae36-f549b714a38a", | 239 | "package_id": "804e1201-067d-4c50-ae36-f549b714a38a", | ||
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| 227 | "size": 33295, | 242 | "size": 33295, | ||
| 228 | "state": "active", | 243 | "state": "active", | ||
| 229 | "url": | 244 | "url": | ||
| 230 | ource/012f1059-1da1-420d-b847-6cf0e621f74d/download/landrvolumes.csv", | 245 | ource/012f1059-1da1-420d-b847-6cf0e621f74d/download/landrvolumes.csv", | ||
| 231 | "url_type": "upload" | 246 | "url_type": "upload" | ||
| 232 | }, | 247 | }, | ||
| 233 | { | 248 | { | ||
| 234 | "cache_last_updated": null, | 249 | "cache_last_updated": null, | ||
| 235 | "cache_url": null, | 250 | "cache_url": null, | ||
| 236 | "created": "2023-12-12T08:02:01.473883", | 251 | "created": "2023-12-12T08:02:01.473883", | ||
| 237 | "datastore_active": false, | 252 | "datastore_active": false, | ||
| 238 | "description": "This dataset comprises preprocessed MRI images | 253 | "description": "This dataset comprises preprocessed MRI images | ||
| 239 | acquired from schizophrenia patients. These images have been processed | 254 | acquired from schizophrenia patients. These images have been processed | ||
| n | 240 | using FSL to generate data on cortical thickness.", | n | 255 | using Freesurfer to generate data on brain structural features.", |
| 241 | "format": "NIFTI", | 256 | "format": "mgz", | ||
| 242 | "hash": "", | 257 | "hash": "", | ||
| 243 | "id": "fe45f10d-ea5b-4af7-9a65-b62bd71c60eb", | 258 | "id": "fe45f10d-ea5b-4af7-9a65-b62bd71c60eb", | ||
| 244 | "last_modified": null, | 259 | "last_modified": null, | ||
| n | 245 | "metadata_modified": "2023-12-12T08:02:31.923112", | n | 260 | "metadata_modified": "2023-12-12T12:06:37.785911", |
| 246 | "mimetype": null, | 261 | "mimetype": null, | ||
| 247 | "mimetype_inner": null, | 262 | "mimetype_inner": null, | ||
| t | 248 | "name": "MRI Cortical Thickness Image Dataset - Schizophrenia", | t | 263 | "name": "MRI Freesurfer Dataset - Schizophrenia", |
| 249 | "package_id": "804e1201-067d-4c50-ae36-f549b714a38a", | 264 | "package_id": "804e1201-067d-4c50-ae36-f549b714a38a", | ||
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| 253 | "state": "active", | 268 | "state": "active", | ||
| 254 | "url": | 269 | "url": | ||
| 255 | hHgmpJx9vJ3E6Hg9dozzyab/uvXeRhty_BrX9JJsvhdi5f-nPPV7Ja7h-GbDA_92r-Ao", | 270 | hHgmpJx9vJ3E6Hg9dozzyab/uvXeRhty_BrX9JJsvhdi5f-nPPV7Ja7h-GbDA_92r-Ao", | ||
| 256 | "url_type": null | 271 | "url_type": null | ||
| 257 | } | 272 | } | ||
| 258 | ], | 273 | ], | ||
| 259 | "state": "active", | 274 | "state": "active", | ||
| 260 | "tags": [ | 275 | "tags": [ | ||
| 261 | { | 276 | { | ||
| 262 | "display_name": "Mental Health", | 277 | "display_name": "Mental Health", | ||
| 263 | "id": "7bb6d9bb-aa78-406e-b708-b17c01c16223", | 278 | "id": "7bb6d9bb-aa78-406e-b708-b17c01c16223", | ||
| 264 | "name": "Mental Health", | 279 | "name": "Mental Health", | ||
| 265 | "state": "active", | 280 | "state": "active", | ||
| 266 | "vocabulary_id": null | 281 | "vocabulary_id": null | ||
| 267 | }, | 282 | }, | ||
| 268 | { | 283 | { | ||
| 269 | "display_name": "bipolar disorder", | 284 | "display_name": "bipolar disorder", | ||
| 270 | "id": "e7c29991-0c6e-4235-b730-8fdacba43171", | 285 | "id": "e7c29991-0c6e-4235-b730-8fdacba43171", | ||
| 271 | "name": "bipolar disorder", | 286 | "name": "bipolar disorder", | ||
| 272 | "state": "active", | 287 | "state": "active", | ||
| 273 | "vocabulary_id": null | 288 | "vocabulary_id": null | ||
| 274 | }, | 289 | }, | ||
| 275 | { | 290 | { | ||
| 276 | "display_name": "brain", | 291 | "display_name": "brain", | ||
| 277 | "id": "7828821f-c0ef-4377-98c3-4261eee91cf1", | 292 | "id": "7828821f-c0ef-4377-98c3-4261eee91cf1", | ||
| 278 | "name": "brain", | 293 | "name": "brain", | ||
| 279 | "state": "active", | 294 | "state": "active", | ||
| 280 | "vocabulary_id": null | 295 | "vocabulary_id": null | ||
| 281 | }, | 296 | }, | ||
| 282 | { | 297 | { | ||
| 283 | "display_name": "brain image", | 298 | "display_name": "brain image", | ||
| 284 | "id": "e6e4b86c-3c9b-43a8-9482-f9d6818cbd5d", | 299 | "id": "e6e4b86c-3c9b-43a8-9482-f9d6818cbd5d", | ||
| 285 | "name": "brain image", | 300 | "name": "brain image", | ||
| 286 | "state": "active", | 301 | "state": "active", | ||
| 287 | "vocabulary_id": null | 302 | "vocabulary_id": null | ||
| 288 | }, | 303 | }, | ||
| 289 | { | 304 | { | ||
| 290 | "display_name": "depression", | 305 | "display_name": "depression", | ||
| 291 | "id": "3263b012-fd20-43ec-8d4b-14d947eb200a", | 306 | "id": "3263b012-fd20-43ec-8d4b-14d947eb200a", | ||
| 292 | "name": "depression", | 307 | "name": "depression", | ||
| 293 | "state": "active", | 308 | "state": "active", | ||
| 294 | "vocabulary_id": null | 309 | "vocabulary_id": null | ||
| 295 | }, | 310 | }, | ||
| 296 | { | 311 | { | ||
| 297 | "display_name": "schizophrenia", | 312 | "display_name": "schizophrenia", | ||
| 298 | "id": "b8c9c52a-d62f-49eb-9d04-5877b53a2c70", | 313 | "id": "b8c9c52a-d62f-49eb-9d04-5877b53a2c70", | ||
| 299 | "name": "schizophrenia", | 314 | "name": "schizophrenia", | ||
| 300 | "state": "active", | 315 | "state": "active", | ||
| 301 | "vocabulary_id": null | 316 | "vocabulary_id": null | ||
| 302 | } | 317 | } | ||
| 303 | ], | 318 | ], | ||
| 304 | "title": "Taiwan Aging and Mental Illness Cohort", | 319 | "title": "Taiwan Aging and Mental Illness Cohort", | ||
| 305 | "type": "dataset", | 320 | "type": "dataset", | ||
| 306 | "url": "", | 321 | "url": "", | ||
| 307 | "version": "" | 322 | "version": "" | ||
| 308 | } | 323 | } |