# Dynamic graph convolutional autoencoder with node-attribute-wise attention for kidney and tumor segmentation from CT volumes

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/dynamic-graph-convolutional-autoencoder-with-node-attribute-wise-attention-for/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ping Xuan,Hui Cui,Hongda Zhang,Tiangang Zhang,Linlin Wang,Toshiya Nakaguchi,Henry Been‐Lirn Duh |
| Citations | 38 |
| DOI | 10.1016/j.knosys.2021.107360 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3187492106 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Toshiya Nakaguchi](https://scholariq.org/researchers/toshiya-nakaguchi/)

## Paper primary topic

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

## Paper topics

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [MRI in cancer diagnosis](https://scholariq.org/topics/mri-in-cancer-diagnosis/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.