{
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"@type": "Dataset",
"@id": "https://doi.org/10.17044/scilifelab.14687271.v1",
"url": "https://scilifelab.figshare.com/articles/dataset/CSAW-M_An_Ordinal_Classification_Dataset_for_Benchmarking_Mammographic_Masking_of_Cancer/14687271/1",
"additionalType": "Dataset",
"name": "CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer",
"author": [
{
"name": "Moein Sorkhei",
"givenName": "Moein",
"familyName": "Sorkhei"
},
{
"name": "Yue Liu",
"givenName": "Yue",
"familyName": "Liu"
},
{
"name": "Hossein Azizpour",
"givenName": "Hossein",
"familyName": "Azizpour",
"@id": "https://orcid.org/0000-0001-5211-6388"
},
{
"name": "Edward Azavedo",
"givenName": "Edward",
"familyName": "Azavedo"
},
{
"name": "Karin Dembrower",
"givenName": "Karin",
"familyName": "Dembrower",
"@id": "https://orcid.org/0000-0001-5966-0749"
},
{
"name": "Dimitra Ntoula",
"givenName": "Dimitra",
"familyName": "Ntoula"
},
{
"name": "Anthanasios Zouzos",
"givenName": "Anthanasios",
"familyName": "Zouzos"
},
{
"name": "Fredrik Strand",
"givenName": "Fredrik",
"familyName": "Strand",
"@id": "https://orcid.org/0000-0003-3910-7086"
},
{
"name": "Kevin Smith",
"givenName": "Kevin",
"familyName": "Smith"
}
],
"description": "Welcome to the the CSAW-M dataset homepage
This page includes the files and metadata related to the CSAW-M, a curated dataset of mammograms with expert assessments of the masking of cancer. CSAW-M is collected from over 10,000 individuals and annotated with potential masking. In contrast to the previous approaches which measure breast image density as a proxy, our dataset directly provides annotations of masking potential assessments from five specialists. We trained deep learning models on CSAW-M to estimate the masking level, and showed that the estimated masking is significantly more predictive of screening participants diagnosed with interval and large invasive cancers — without being explicitly trained for these tasks — than its breast density counterparts. Please find the paper corresponding to our work here and the GitHub repo here.Terms of use:
Our dataset is licensed under CC BY-NC-ND 4.0 for non-commercial use only, and for research related to that of this work. Here we ask users to agree to our terms and conditions when requesting the dataset.I request access to the CSAW-M dataset for research purposes and agree to the following terms: I will not share the download link with anybody. I will not attempt to re-identify the subjects or use the data for any illegal purposes. In the unlikely case of re-identification of any individuals in the dataset, I will immediately inform the authors. Upon request from the authors at any time, I am obliged to delete any copy of the data I have. I will require anyone in my team who uses this data, or whoever I share the data with, to comply with the terms mentioned on this page. By filling the request form, I will allow the authors to keep the information I provide (which is used by the authors to simply keep a record of who requested the dataset). Also, I will allow the authors to use this information to contact me (e.g. in case the dataset is updated). I understand that the terms of use mentioned on this page are subject to change. I will be informed about such changes and comply with them. If I violate any of the terms above, I will immediately delete the data and will not retain any portion of it. By sending a request to access the dataset, I agree to all the above-mentioned terms. How to access the dataset:
If you want to get access to the data, please use the \"Request access to files\" option that will appear above soon (currently, non-Swedish researchers need to have a general figshare account to be able to to request access). We will ask you to agree to our terms of conditions and provide us with some information about what you will use the data for. We will then receive the request and process it, after which you would be able to download all the files.",
"license": "https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode",
"keywords": "80104 Computer Vision, FOS: Computer and information sciences, Artificial Intelligence and Image Processing",
"contentSize": "2673414633 Bytes",
"dateCreated": "2021-10-12",
"datePublished": "2021",
"dateModified": "2021-12-03",
"predecessor_of": {
"@id": "https://doi.org/10.17044/scilifelab.14687271",
"@type": "CreativeWork"
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"publisher": {
"@type": "Organization",
"name": "SciLifeLab"
},
"provider": {
"@type": "Organization",
"name": "datacite"
}
}