# Automatic Segmentation of Kidney and Renal Tumor in CT Images Based on 3D Fully Convolutional Neural Network with Pyramid Pooling Module

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/automatic-segmentation-of-kidney-and-renal-tumor-in-ct-images-based-on-3d-fully/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Guanyu Yang,Guoqing Li,Tan Pan,Youyong Kong,Jiasong Wu,Huazhong Shu,Limin Luo,Jean‐Louis Dillenseger,Jean-Louis Coatrieux,Lijun Tang,Xiaomei Zhu |
| Citations | 81 |
| DOI | 10.1109/icpr.2018.8545143 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://univ-rennes.hal.science/hal-02036719 |
| OpenAlex ID | https://openalex.org/W2902878689 |
| Type | conference-paper |
| Year | 2018 |

## Paper authors

- [Lijun Tang](https://scholariq.org/researchers/lijun-tang/)

## 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/)
- [Renal cell carcinoma treatment](https://scholariq.org/topics/renal-cell-carcinoma-treatment/)

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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.