cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.xnpcno
title: Occurrence Download

description: A dataset containing 5861 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lygodium venustum Sw."
 ]
}

 The dataset includes 5861 records from 191 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026639-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34816/ifao.archives.72953
title: CACHETTE DE KARNAK - CK_417_nu_2010_06045

description: Référence : nu_2010_06045<br />Site : Karnak<br />Type : photographie<br />
DOI: 10.15468/dl.q7g25w
title: Occurrence Download

description: A dataset containing 49401 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is North Carolina State University Insect Collection"
 ]
}

 The dataset includes 49401 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0100474-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.438ubj
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sphenophryne schlaginhaufeni Wandolleck, 1911"
 ]
}

 The dataset includes 61 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0303321-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34816/ifao.archives.72952
title: CACHETTE DE KARNAK - CK_417_nu_2010_06044

description: Référence : nu_2010_06044<br />Site : Karnak<br />Type : photographie<br />
DOI: 10.34816/ifao.archives.72951
title: CACHETTE DE KARNAK - CK_417_nu_2010_06043

description: Référence : nu_2010_06043<br />Site : Karnak<br />Type : photographie<br />
DOI: 10.15468/dl.aqa9eq
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Dysphania ambrosioides (L.) Mosyakin & Clemants"
 ]
}

 The dataset includes 96 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088120-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34816/ifao.archives.72950
title: CACHETTE DE KARNAK - CK_417_nu_2010_06042

description: Référence : nu_2010_06042<br />Site : Karnak<br />Type : photographie<br />
DOI: 10.15468/dl.xn68a8
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sporobolus engleri Pilg."
 ]
}

 The dataset includes 51 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0139802-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34816/ifao.archives.72949
title: CACHETTE DE KARNAK - CK_417_nu_2010_06041

description: Référence : nu_2010_06041<br />Site : Karnak<br />Type : photographie<br />
DOI: 10.15468/dl.pe3hns
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gastrotheca dysprosita Duellman, 2013"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0303280-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ert4dg
title: Occurrence Download

description: A dataset containing 78 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Pistia stratiotes L."
 ]
}

 The dataset includes 78 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085830-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.798xdn
title: Occurrence Download

description: A dataset containing 105 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "StateProvince is one of (cauca)",
 "TaxonKey is one of (Trichomycterus Valenciennes, 1832)"
 ]
 }
 ]
}

 The dataset includes 105 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008841-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fvny6u
title: Occurrence Download

description: A dataset containing 8261 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acronicta euphorbiae (Denis & Schiffermüller), 1775, Acronicta menyanthidis (Esper))",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 8261 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0308934-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m9b8rh
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Caloptilia theivora (Walsingham, 1891)",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0209181-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.czv59s
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tetranema floribundum Hammel & Grayum"
 ]
}

 The dataset includes 25 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011403-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yv2r64
title: Occurrence Download

description: A dataset containing 809858 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Specimen"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Betulaceae",
 "Year 1900-1990"
 ]
}

 The dataset includes 809858 records from 548 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0384990-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hacuq2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Hordeum capense",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030363-250525065834625/datasets/export for details.
DOI: 10.15468/dl.t62xvv
title: Occurrence Download

description: A dataset containing 628 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Triatoma gerstaeckeri (Stål, 1859)"
 ]
}

 The dataset includes 628 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018233-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11386975
title: ReMIND2Reg dataset (2023)

description: Official training and validation sets of ReMIND2Reg 2024.

The goal of the ReMIND2Reg dataset is to address the registration problem of multi-parametric pre-operative MRI and intra-operative 3D ultrasound (iUS) images. Specifically, we focus on the challenging problem of pre-operative to post-resection registration, requiring the estimation of large deformations and tissue resections. Preoperative MRI comprises two structural MRI sequences: contrast-enhanced T1-weighted (ceT1) and native T2-weighted (T2). However, not all sequences are available for all cases. For this reason, developed methods must have the flexibility to leverage incomplete data sets at inference time. 

The released data corresponds to a modified (pre-processed) subset of the Brain Resection Multimodal Imaging Database (ReMIND) from The Cancer Imaging Archive, released with a CC BY 4.0 license, which contains pre- and intra-operative data collected on 114 consecutive patients who were surgically treated with image-guided tumor resection between 2018 and 2022: https://doi.org/10.7937/3rag-d070.

For each patient, 3D intraoperative ultrasound data reconstructed from tracked 2D sweep were acquired during brain surgery after substantial tumor resection was completed to the degree that either the surgeon was satisfied with the microscopically-visible extent of resection or to identify the remaining portion of the tumor (_0000.nii.gz). Before surgery, contrast-enhanced T1 (ceT1) MR scans (_0001.nii.gz) and/or T2-SPACE (_0002.nii.gz) were acquired to identify the surgical target. 

The task is to find one solution for the registration of two pairs of images per patient:1. 3D post-resection iUS and ceT12. 3D post-resection iUS and T2

The two main challenges are the significant variations in intensity distribution and local information between two imaging modalities (iUS and MR) and the estimation of large deformations with topological changes due to tissue resections. 

The released dataset includes training images of 99 patients with 99 3D iUS, 93 ceT1, and 62 T2, and validation images of 5 patients with 5 3D US, 5 ceT1, and 5 T2. The images are paired as described above with two image pairs per patient, resulting in 1585image pairs for training and 10 image pairs for validation. 

For details on the image acquisition (scanner details, etc.), please see https://doi.org/10.1101/2023.09.14.23295596.

All images are converted to NIfTI. When more than one pre-operative MR sequence was available, ceT1 was affinely co-registered to the T2 using NiftyReg; Ultrasound images were resampled in the pre-operative MR space. Images were cropped in the field of view of the iUS in an image size of 256x256x256 with a spacing of 0.5x0.5x0.5mm.

 

Data citation:Juvekar, P., Dorent, R., Kögl, F., Torio, E., Barr, C., Rigolo, L., Galvin, C., Jowkar, N., Kazi, A., Haouchine, N., Cheema, H., Navab, N., Pieper, S., Wells, W. M., Bi, W. L., Golby, A., Frisken, S., & Kapur, T. (2023). The Brain Resection Multimodal Imaging Database (ReMIND) (Version 1) [dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/3rag-d070.
DOI: 10.5281/zenodo.11098847
title: ReMIND2Reg dataset (2023)

description: Official training and validation sets of ReMIND2Reg 2024.

The goal of the ReMIND2Reg dataset is to address the registration problem of multi-parametric pre-operative MRI and intra-operative 3D ultrasound (iUS) images. Specifically, we focus on the challenging problem of pre-operative to post-resection registration, requiring the estimation of large deformations and tissue resections. Preoperative MRI comprises two structural MRI sequences: contrast-enhanced T1-weighted (ceT1) and native T2-weighted (T2). However, not all sequences are available for all cases. For this reason, developed methods must have the flexibility to leverage incomplete data sets at inference time. 

The released data corresponds to a modified (pre-processed) subset of the Brain Resection Multimodal Imaging Database (ReMIND) from The Cancer Imaging Archive, released with a CC BY 4.0 license, which contains pre- and intra-operative data collected on 114 consecutive patients who were surgically treated with image-guided tumor resection between 2018 and 2022: https://doi.org/10.7937/3rag-d070.

For each patient, 3D intraoperative ultrasound data reconstructed from tracked 2D sweep were acquired during brain surgery after substantial tumor resection was completed to the degree that either the surgeon was satisfied with the microscopically-visible extent of resection or to identify the remaining portion of the tumor (_0000.nii.gz). Before surgery, contrast-enhanced T1 (ceT1) MR scans (_0001.nii.gz) and/or T2-SPACE (_0002.nii.gz) were acquired to identify the surgical target. 

The task is to find one solution for the registration of two pairs of images per patient:1. 3D post-resection iUS and ceT12. 3D post-resection iUS and T2

The two main challenges are the significant variations in intensity distribution and local information between two imaging modalities (iUS and MR) and the estimation of large deformations with topological changes due to tissue resections . 

The released dataset includes training images of 99 patients with 99 3D iUS, 93 ceT1, and 62 T2, and validation images of 5 patients with 5 3D US, 5 ceT1, and 5 T2. The images are paired as described above with two image pairs per patient, resulting in 1585image pairs for training and 10 image pairs for validation. 

For details on the image acquisition (scanner details, etc.), please see https://doi.org/10.1101/2023.09.14.23295596.

All images are converted to NIfTI. When more than one pre-operative MR sequence was available, ceT1 was affinely co-registered to the T2 using NiftyReg; Ultrasound images were resampled in the pre-operative MR space. Images were cropped in the field of view of the iUS in an image size of 256x256x256 with a spacing of 0.5x0.5x0.5mm.

 

Data citation:Juvekar, P., Dorent, R., Kögl, F., Torio, E., Barr, C., Rigolo, L., Galvin, C., Jowkar, N., Kazi, A., Haouchine, N., Cheema, H., Navab, N., Pieper, S., Wells, W. M., Bi, W. L., Golby, A., Frisken, S., & Kapur, T. (2023). The Brain Resection Multimodal Imaging Database (ReMIND) (Version 1) [dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/3rag-d070.
DOI: 10.5281/zenodo.11098848
title: ReMIND2Reg dataset (2023)

description: Official training and validation sets of ReMIND2Reg 2024.

The goal of the ReMIND2Reg dataset is to address the registration problem of multi-parametric pre-operative MRI and intra-operative 3D ultrasound (iUS) images. Specifically, we focus on the challenging problem of pre-operative to post-resection registration, requiring the estimation of large deformations and tissue resections. Preoperative MRI comprises two structural MRI sequences: contrast-enhanced T1-weighted (ceT1) and native T2-weighted (T2). However, not all sequences are available for all cases. For this reason, developed methods must have the flexibility to leverage incomplete data sets at inference time. 

The released data corresponds to a modified (pre-processed) subset of the Brain Resection Multimodal Imaging Database (ReMIND) from The Cancer Imaging Archive, released with a CC BY 4.0 license, which contains pre- and intra-operative data collected on 114 consecutive patients who were surgically treated with image-guided tumor resection between 2018 and 2022: https://doi.org/10.7937/3rag-d070.

For each patient, 3D intraoperative ultrasound data reconstructed from tracked 2D sweep were acquired during brain surgery after substantial tumor resection was completed to the degree that either the surgeon was satisfied with the microscopically-visible extent of resection or to identify the remaining portion of the tumor (_0000.nii.gz). Before surgery, contrast-enhanced T1 (ceT1) MR scans (_0001.nii.gz) and/or T2-SPACE (_0002.nii.gz) were acquired to identify the surgical target. 

The task is to find one solution for the registration of two pairs of images per patient:1. 3D post-resection iUS and ceT12. 3D post-resection iUS and T2

The two main challenges are the significant variations in intensity distribution and local information between two imaging modalities (iUS and MR) and the estimation of large deformations with topological changes due to tissue resections. 

The released dataset includes training images of 99 patients with 99 3D iUS, 93 ceT1, and 65 T2, and validation images of 5 patients with 5 3D US, 5 ceT1, and 5 T2. The images are paired as described above with two image pairs per patient, resulting in 158 image pairs for training and 10 image pairs for validation. 

For details on the image acquisition (scanner details, etc.), please see https://doi.org/10.1101/2023.09.14.23295596.

All images are converted to NIfTI. When more than one pre-operative MR sequence was available, ceT1 was affinely co-registered to the T2 using NiftyReg; Ultrasound images were resampled in the pre-operative MR space. Images were cropped in the field of view of the iUS in an image size of 256x256x256 with a spacing of 0.5x0.5x0.5mm.

 

Data citation:Juvekar, P., Dorent, R., Kögl, F., Torio, E., Barr, C., Rigolo, L., Galvin, C., Jowkar, N., Kazi, A., Haouchine, N., Cheema, H., Navab, N., Pieper, S., Wells, W. M., Bi, W. L., Golby, A., Frisken, S., & Kapur, T. (2023). The Brain Resection Multimodal Imaging Database (ReMIND) (Version 1) [dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/3rag-d070.
DOI: 10.5281/zenodo.11387725
title: ReMIND2Reg dataset (2023)

description: Official training and validation sets of ReMIND2Reg 2024.

The goal of the ReMIND2Reg dataset is to address the registration problem of multi-parametric pre-operative MRI and intra-operative 3D ultrasound (iUS) images. Specifically, we focus on the challenging problem of pre-operative to post-resection registration, requiring the estimation of large deformations and tissue resections. Preoperative MRI comprises two structural MRI sequences: contrast-enhanced T1-weighted (ceT1) and native T2-weighted (T2). However, not all sequences are available for all cases. For this reason, developed methods must have the flexibility to leverage incomplete data sets at inference time. 

The released data corresponds to a modified (pre-processed) subset of the Brain Resection Multimodal Imaging Database (ReMIND) from The Cancer Imaging Archive, released with a CC BY 4.0 license, which contains pre- and intra-operative data collected on 114 consecutive patients who were surgically treated with image-guided tumor resection between 2018 and 2022: https://doi.org/10.7937/3rag-d070.

For each patient, 3D intraoperative ultrasound data reconstructed from tracked 2D sweep were acquired during brain surgery after substantial tumor resection was completed to the degree that either the surgeon was satisfied with the microscopically-visible extent of resection or to identify the remaining portion of the tumor (_0000.nii.gz). Before surgery, contrast-enhanced T1 (ceT1) MR scans (_0001.nii.gz) and/or T2-SPACE (_0002.nii.gz) were acquired to identify the surgical target. 

The task is to find one solution for the registration of two pairs of images per patient:1. 3D post-resection iUS and ceT12. 3D post-resection iUS and T2

The two main challenges are the significant variations in intensity distribution and local information between two imaging modalities (iUS and MR) and the estimation of large deformations with topological changes due to tissue resections . 

The released dataset includes training images of 99 patients with 99 3D iUS, 93 ceT1, and 62 T2, and validation images of 5 patients with 5 3D US, 5 ceT1, and 5 T2. The images are paired as described above with two image pairs per patient, resulting in 1585image pairs for training and 10 image pairs for validation. 

For details on the image acquisition (scanner details, etc.), please see https://doi.org/10.1101/2023.09.14.23295596.

All images are converted to NIfTI. When more than one pre-operative MR sequence was available, ceT1 was affinely co-registered to the T2 using NiftyReg; Ultrasound images were resampled in the pre-operative MR space. Images were cropped in the field of view of the iUS in an image size of 256x256x256 with a spacing of 0.5x0.5x0.5mm.

 

Data citation:Juvekar, P., Dorent, R., Kögl, F., Torio, E., Barr, C., Rigolo, L., Galvin, C., Jowkar, N., Kazi, A., Haouchine, N., Cheema, H., Navab, N., Pieper, S., Wells, W. M., Bi, W. L., Golby, A., Frisken, S., & Kapur, T. (2023). The Brain Resection Multimodal Imaging Database (ReMIND) (Version 1) [dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/3rag-d070.