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...
| Автори: | , , , , |
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| Формат: | Conference item |
| Мова: | English |
| Опубліковано: |
IEEE
2023
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