Efficient Multi-Organ Segmentation From 3D Abdominal CT Images With Lightweight Network and Knowledge Distillation-Reference-Cited by-同舟云学术

Efficient Multi-Organ Segmentation From 3D Abdominal CT Images With Lightweight Network and Knowledge Distillation

Author:

Zhao Qianfei¹,Zhong Lanfeng¹,Xiao Jianghong²,Zhang Jingbo³,Chen Yinan⁴^ORCID,Liao Wenjun⁵,Zhang Shaoting¹,Wang Guotai¹^ORCID

Affiliation:

1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China

2. Department of Radiation Oncology, Cancer Center West China Hospital, Sichuan University, Chengdu, China

3. Centre for Perceptual and Interactive Intelligence (CPII), Hong Kong, China

4. SenseTime Research, Shanghai, China

5. Sichuan Cancer Hospital, University of Electronic Science and Technology of China, Chengdu, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

Reference51 articles.

4. Distilling the knowledge in a neural network;hinton;Proc NIPS,2014

5. S3D-UNet: Separable 3D U-Net for brain tumor segmentation;chen;Proc MICCAI BrainLesion Workshop,2018

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