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MIDRC-RICORD-1C

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DOI: 10.7937/91ah-v663 | Image Collection

Background

The COVID-19 pandemic is a global healthcare emergency. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making in imaging. However, inadequate availability of a diverse annotated dataset has limited the performance and generalizability of existing models.

Purpose

To create the first multi-institutional, multi-national expert annotated COVID-19...

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MIDRC-RICORD-1B

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DOI: 10.7937/31V8-4A40 | Image Collection

Background

The COVID-19 pandemic is a global healthcare emergency. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making in imaging. However, inadequate availability of a diverse annotated dataset has limited the performance and generalizability of existing models.

Purpose

To create the first multi-institutional, multi-national expert annotated...

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MIDRC-RICORD-1A

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DOI: 10.7937/VTW4-X588 | Image Collection

Background

The COVID-19 pandemic is a global healthcare emergency. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making in imaging. However, inadequate availability of a diverse annotated dataset has limited the performance and generalizability of existing models.

Purpose

The Radiological Society of North America (RSNA) assembled the RSNA...

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HEALTHY-TOTAL-BODY-CTS

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DOI: 10.7937/NC7Z-4F76 | Image Collection

This data set includes low-dose whole body CT images and tissue segmentations of thirty healthy adult research participants who underwent PET/CT imaging on the uEXPLORER total-body PET/CT system at UC Davis. Participants included in this study were healthy adults, 18 years of age or older, who were able to provide informed written consent. The participants' age, sex, weight, height, and body mass index are also provided.

Fifteen...

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LDCT-AND-PROJECTION-DATA

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DOI: 10.7937/9NPB-2637 | Image Collection

Investigators at the Mayo Clinic, with funding from the National Institute of Biomedical Imaging and Bioengineering (EB 017095 and EB 017185), have built a library of CT patient projection data in an open and vendor-neutral format. This format, referred to as DICOM-CT-PD (Additional information regarding the CT projection data format in the article by Chen et al at doi:

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LGG-1P19QDELETION

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DOI: 10.7937/K9/TCIA.2017.DWEHTZ9V | Image Collection

These MRIs are pre-operative examinations performed in 159 subjects with Low Grade Gliomas (WHO grade II & III). Segmentation of tumors in three axial slices that include the one with the largest tumor diameter and ones below and above are provided in NiFTI format.  Tumor grade and histologic type are also available.  All of these subjects have biopsy proven 1p/19q results, performed using FISH.  For the...

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IVYGAP

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DOI: 10.7937/K9/TCIA.2016.XLwaN6nL | Image Collection

This data collection consists of MRI/CT scan data for brain tumor patients that form the cohort for the resource Ivy Glioblastoma Atlas Project (Ivy GAP). There are 390 studies for 39 patients that include pre-surgery, post-surgery and follow up scans. The Ivy GAP is a collaborative partnership between the Ben and Catherine Ivy Foundation, which generously provided the financial...

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