Localtab |
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active | true |
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title | Data Access |
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| Data Access
Data Type | Download all or Query/Filter | License |
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Images (JPG, 196MB) |
Tcia button generator |
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url | https://faspex.cancerimagingarchive.net/aspera/faspex/external_deliveries/70?passcode=93cc61a4c4ae53aa503b26d8c87badd592e75fd2 |
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Tcia button generator |
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label | Search |
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url | https://pathdb.cancerimagingarchive.net/imagesearch?f[0]=collection:osteosarcoma_tumor_assessment |
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(Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) | | Features (CSV, 860 kB) |
Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/52756935/ML_Features_1144.csv?version=1&modificationDate=1613057224752&api=v2 |
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Click the Versions tab for more info about data releases. |
Localtab |
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title | Detailed Description |
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| Detailed Description | |
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Modalities | Pathology | Number of Participants | 4 | Number of Images | 1144 | Images Size (MB) | 196 | Folder_Structure- Data_Osteo_Files
- ML_Features_1144.csv - Contains 1144 rows for all the image tiles and 69 columns for filename, classification, and 65 machine learning features.
- Training_Set_1 - 11 folders with 547 images. Each folder contains 48~50 image tiles and 1 csv for annotation.
- set 1- 49 Image Tiles
- set 2- 50 Image Tiles
- set 3- 50 Image Tiles
- set 4- 50 Image Tiles
- set 5- 50 Image Tiles
- set 6- 50 Image Tiles
- set 7- 50 Image Tiles
- set 8- 50 Image Tiles
- set 9- 50 Image Tiles
- set 10- 50 Image Tiles
- set 11- 48 Image Tiles
- Training_Set_2 - 12 folders with 597 images. Each folder contains 48~50 image tiles and 1 csv for annotation.
- set 1- 49 Image Tiles
- set 2- 50 Image Tiles
- set 3- 50 Image Tiles
- set 4- 50 Image Tiles
- set 5- 50 Image Tiles
- set 6- 50 Image Tiles
- set 7- 50 Image Tiles
- set 8- 50 Image Tiles
- set 9- 50 Image Tiles
- set 10- 50 Image Tiles
- set 11- 50 Image Tiles
- set 12- 48 Image Tiles
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Localtab |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy Tcia limited license policy |
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Info |
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| Leavey, P., Sengupta, A., Rakheja, D., Daescu, O., Arunachalam, H. B., & Mishra, R. (2019). Osteosarcoma data from UT Southwestern/UT Dallas for Viable and Necrotic Tumor Assessment [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/tcia.2019.bvhjhdas |
Info |
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title | Publication Citation |
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| Mishra, R., Daescu, O., Leavey, P., Rakheja, D., & Sengupta, A. (2017). Histopathological Diagnosis for Viable and Non-viable Tumor Prediction for Osteosarcoma Using Convolutional Neural Network. In Bioinformatics Research and Applications (pp. 12–23). Springer International Publishing. https://doi.org/10.1007/978-3-319-59575-7_2 |
Info |
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title | Publication Citation |
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| Arunachalam, H. B., Mishra, R., Armaselu, B., Daescu, O., Martinez, M., Leavey, P., Rakheja, D., Cederberg, K., Sengupta, A., & Ni’suilleabhain, M. (2016). COMPUTER AIDED IMAGE SEGMENTATION AND CLASSIFICATION FOR VIABLE AND NON-VIABLE TUMOR IDENTIFICATION IN OSTEOSARCOMA. In Biocomputing 2017. Proceedings of the Pacific Symposium. WORLD SCIENTIFIC. https://doi.org/10.1142/9789813207813_0020 |
Info |
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title | Publication Citation |
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| Mishra, R., Daescu, O., Leavey, P., Rakheja, D., & Sengupta, A. (2018). Convolutional Neural Network for Histopathological Analysis of Osteosarcoma. In Journal of Computational Biology (Vol. 25, Issue 3, pp. 313–325). Mary Ann Liebert Inc. https://doi.org/10.1089/cmb.2017.0153 |
Info |
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title | Publication Citation |
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| Leavey, P., Arunachalam, H.B., Armaselu, B., Sengupta, A., Rakheja, D., Skapek, S., Cederberg, K., Bach, J.P., Glick, S., Ni'Suilleabhain, M. and Mishra, R., "Implementation of Computer-Based Image Pattern Recognition Algorithms to Interpret Tumor Necrosis; a First Step in Development of a Novel Biomarker in Osteosarcoma." PEDIATRIC BLOOD & CANCER. Vol. 64. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY, 2017. |
Info |
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| Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. Journal of Digital Imaging, 26(6), 1045–1057. https://doi.org/10.1007/s10278-013-9622-7 |
Other Publications Using This DataTCIA maintains a list of publications which leverage our data. If you have a manuscript you'd like to add please contact TCIA's Helpdesk. |
Localtab |
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| Version 1 (Current): Updated 2019/03/22
Data Type | Download all or Query/Filter |
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Images (JPG, 196MB) |
Tcia button generator |
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url | https://faspex.cancerimagingarchive.net/aspera/faspex/external_deliveries/70?passcode=93cc61a4c4ae53aa503b26d8c87badd592e75fd2 |
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Tcia button generator |
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label | Search |
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url | https://pathdb.cancerimagingarchive.net/imagesearch?f[0]=collection:osteosarcoma_tumor_assessment |
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(Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) | Features (CSV) |
Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/52756935/ML_Features_1144.csv?version=1&modificationDate=1613057224752&api=v2 |
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