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CMB-PCA

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DOI: 10.7937/25T7-6Y12 | Image Collection

The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...

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CMB-MML

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DOI: 10.7937/SZKB-SW39 | Image Collection

The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...

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CMB-MEL

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DOI: 10.7937/GWSP-WH72 | Image Collection

The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...

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CMB-LCA

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DOI: 10.7937/3CX3-S132 | Image Collection

The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...

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CMB-GEC

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DOI: 10.7937/E7KH-R486 | Image Collection

The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...

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CMB-CRC

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DOI: 10.7937/DJG7-GZ87 | Image Collection

The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...

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CMB-AML

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DOI: 10.7937/PCTE-6M66 | Image Collection

The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...

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BURDENKO-GBM-PROGRESSION

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DOI: 10.7937/E1QP-D183 | Image Collection

The Burdenko Glioblastoma Progression Dataset (BGPD) is a systematic data collection from 180 patients with primary glioblastoma treated at the Burdenko National Medical Research Center of Neurosurgery between 2014 and 2020. 

For each patient, the dataset includes imaging studies conducted for radiotherapy planning and follow-up studies. The radiotherapy studies consist of 4 MRI sequences (T1, T1C, T2, FLAIR),...

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PANCREATIC-CT-CBCT-SEG

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DOI: 10.7937/TCIA.ESHQ-4D90 | Image Collection

Accurate deformable registration between CT and cone-beam CT (CBCT) images of pancreatic cancer patients treated with high radiation doses is highly desirable for assessing changes in organ-at-risk (OAR) locations and shapes at treatment. The objective of this dataset is to provide a means of evaluating the performance of CT-to-CBCT deformable registration and auto-segmentation algorithms for delineating OARs. The...

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SLN-BREAST

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DOI: 10.7937/tcia.2019.3xbn2jcc | Image Collection

The detection of breast cancer metastases to lymph nodes is of great prognostic value for patient treatment. Using machine learning to detect metastatic breast cancer to lymph nodes can increase efficiency of pathologist diagnosis and ultimately ensure patients are accurately staged for prospective treatment. This dataset allows for the objective comparison of breast cancer metastases detection algorithms.

The...

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