GA-UNet: UNet-based framework for segmentation of 2D and 3D medical images applicable on heterogeneous datasets

A Kaur, L Kaur, A Singh - Neural Computing and Applications, 2021 - Springer
Segmentation of biomedical images is the method of semiautomatic and automatic detection
of boundaries within 2D and 3D images. The major challenge of medical image …
被引用次数：30 相关文章
[PDF] researchgate.net

[PDF][PDF] GA-UNet: UNet-based framework for segmentation of 2D and 3D medical images applicable on heterogeneous datasets

A Kaur, L Kaur, A Singh - researchgate.net
Segmentation of biomedical images is the method of semiautomatic and automatic detection
of boundaries within 2D and 3D images. The major challenge of medical image …

GA-UNet: UNet-based framework for segmentation of 2D and 3D medical images applicable on heterogeneous datasets

A Kaur, L Kaur, A Singh - Neural Computing and Applications, 2021 - dl.acm.org
Segmentation of biomedical images is the method of semiautomatic and automatic detection
of boundaries within 2D and 3D images. The major challenge of medical image …

GA-UNet: UNet-based framework for segmentation of 2D and 3D medical images applicable on heterogeneous datasets.

A Kaur, L Kaur, A Singh - Neural Computing & Applications, 2021 - search.ebscohost.com
Segmentation of biomedical images is the method of semiautomatic and automatic detection
of boundaries within 2D and 3D images. The major challenge of medical image …

GA-UNet: UNet-based framework for segmentation of 2D and 3D medical images applicable on heterogeneous datasets

K Amrita, K Lakhwinder, A Singh - Neural Computing & …, 2021 - search.proquest.com
Segmentation of biomedical images is the method of semiautomatic and automatic detection
of boundaries within 2D and 3D images. The major challenge of medical image …