CNSEG-GAN: a lightweight generative adversarial network for segmentation of CRL and NT from first-trimester fetal ultrasound

This paper presents a novel, low-compute and efficient generative adversarial network (GAN) design for automatic segmentation called CNSeg-GAN, which combines 1-D kernel factorized networks, spatial and channel attention, and multi-scale aggregation mechanisms in a conditional GAN (cGAN) fashion. Th...

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書目詳細資料
Main Authors: Sarker, MD, Yasrab, R, Alsharid, M, Papageorghiou, A, Noble, J
格式: Conference item
語言:English
出版: IEEE 2023