Efficient Multi-Organ Segmentation from 3D Abdominal CT Images with Lightweight Network and Knowledge Distillation

Accurate segmentation of multiple abdominal organs from Computed Tomography (CT) images plays an important role in computer-aided diagnosis, treatment planning and follow-up. Currently, 3D Convolution Neural Networks (CNN) have achieved promising performance for automatic medical image segmentation...

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Veröffentlicht in:	IEEE transactions on medical imaging 2023-09, Vol.PP (9), p.1-1
Hauptverfasser:	Zhao, Qianfei, Zhong, Lanfeng, Xiao, Jianghong, Zhang, Jingbo, Chen, Yinan, Liao, Wenjun, Zhang, Shaoting, Wang, Guotai
Format:	Artikel
Sprache:	eng
Schlagworte:	Abdomen abdominal organs Accuracy Artificial neural networks Computational efficiency Computed tomography Computer applications Computing costs Convolution Distillation Floating point arithmetic Image processing Image segmentation knowledge distillation Lightweight lightweight CNNs Mathematical models Medical diagnosis Medical diagnostic imaging Medical imaging Neural networks Parameters segmentation Solid modeling Strategy Three dimensional models Three-dimensional displays
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