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Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.

Xianling Dong | Shiqi Xu | Yanli Liu | Aihui Wang | M Iqbal Saripan | Li Li | Xiaolei Zhang | Lijun Lu
Cancer imaging : the official publication of the International Cancer Imaging Society | 2020

Convolutional neural networks (CNNs) have been extensively applied to two-dimensional (2D) medical image segmentation, yielding excellent performance. However, their application to three-dimensional (3D) nodule segmentation remains a challenge.

Pubmed ID: 32738913

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Cancer Imaging Archive (TCIA) (tool)

RRID:SCR_008927

Archive of medical images of cancer accessible for public download. All images are stored in DICOM file format and organized as Collections, typically patients related by common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. Neuroimaging data sets include clinical outcomes, pathology, and genomics in addition to DICOM images. Submitting Data Proposals are welcomed.

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