Author:
Challagundla Yagnesh,Tunuguntla Trilok Sai Charan,Tunuguntla Sindhu Gayathri,Devarakonda Nagaraju
Publisher
Springer Science and Business Media LLC
Reference16 articles.
1. Yoshihiro Y et al (2017) Detection of liver tumor candidates from CT images using deep convolutional neural networks. In: International conference on innovation in medicine and healthcare. Springer, Cham
2. Sidra Gul et al (2022) Deep learning techniques for liver and liver tumor segmentation: a review. Comput Bio Med 147:105620
3. Zhen S et al (2020) Deep learning for accurate diagnosis of liver tumor based on magnetic resonance imaging and clinical data. Front Oncol 10:680
4. Li W (2015) Automatic segmentation of liver tumor in CT images with deep convolutional neural networks. J Comput Commun 3(11):146
5. Hyunseok Seo et al (2019) Modified U-Net (mU-Net) with incorporation of object-dependent high level features for improved liver and liver-tumor segmentation in CT images. IEEE Trans Med Imaging 39(5):1316–1325
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