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</tr> </tr>
<tr><td colspan="2"><a href="survey-and-review">3. Survey And Review</a></td></tr> <tr><td colspan="2"><a href="survey-and-review">3. Survey And Review</a></td></tr>
<tr><td colspan="2"><a href="related-research-platform">4. Related Research Platform</a></td></tr> <tr><td colspan="2"><a href="related-research-platform">4. Related Research Platform</a></td></tr>
<tr><td colspan="2"><a href="public-data">5. Public Data</a></td></tr>
</table> </table>
## [Theory](#content) ## [Theory](#content)
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+ [中国科学院分子影像重点实验室](http://www.radiomics.net.cn/blog/3) + [中国科学院分子影像重点实验室](http://www.radiomics.net.cn/blog/3)
+ [Radiology](https://pubs.rsna.org/journal/radiology) + [Radiology](https://pubs.rsna.org/journal/radiology)
+ [混合成像系统实验室](http://www.hislab.cn/publication) + [混合成像系统实验室](http://www.hislab.cn/publication)
+[南佛罗里达大学工程学院计算机视觉与模式识别小组](http://www.eng.usf.edu/cvprg/)
## [Public Data](#content)
+[ISBI（生物医学成像国际研讨会）每届数据下载地址](https://grand-challenge.org/challenges/)
+[哈佛beamandrew机器学习和医学影像研究者贡献的数据集](https://github.com/beamandrew/medical-data)
+[心脏病心房图像及标注数据](http://dataju.cn/Dataju/web/datasetInstanceDetail/121)
+[癌症CT影像数据](http://dataju.cn/Dataju/web/datasetInstanceDetail/275)
+[软组织肉瘤CT图像数据](http://dataju.cn/Dataju/web/datasetInstanceDetail/284)
+[肺癌CT图像数据](http://dataju.cn/Dataju/web/datasetInstanceDetail/291)
+[癌症MRI影像数据](http://dataju.cn/Dataju/web/datasetInstanceDetail/317)
+[MICCAI胰腺分割数据集](http://medicaldecathlon.com/)
+[The National Library of Medicine presents MedPix](https://medpix.nlm.nih.gov/home)
+[结肠癌CT数据](https://wiki.cancerimagingarchive.net/display/Public/CT+COLONOGRAPHY#dc149b9170f54aa29e88f1119e25ba3e)
+[AMRG Cardiac Atlas（心脏MRI图像）](http://www.cardiacatlas.org/studies/amrg-cardiac-atlas/)
+[大脑MRI数据集](http://www.oasis-brains.org/)
+[肺部图像数据库联盟](https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI)
+[INbreast：数字化乳腺摄影数据库](http://medicalresearch.inescporto.pt/breastresearch/index.php/Get_INbreast_Database)
+[前列腺癌数据集](http://www.ehealthlab.cs.ucy.ac.cy/index.php/facilities/32-software/218-datasets)
+[DeepLesion:多类别、病灶级别标注临床医疗CT图像开放数据集（230G）](https://academictorrents.com/details/de50f4d4aa3d028944647a56199c07f5fa6030ff)
+[MURA:基于深度学习检测骨骼疾病(吴恩达团队公布)](https://www.groundai.com/project/mura-dataset-towards-radiologist-level-abnormality-detection-in-musculoskeletal-radiographs/3)