CEDRNN: A Convolutional Encoder-Decoder Residual Neural Network for Liver Tumour Segmentation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
https://link.springer.com/content/pdf/10.1007/s11063-022-10953-z.pdf
Reference32 articles.
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2. Nadarevic T, Giljaca V, Colli A et al (2019) Computed tomography for the diagnosis of hepatocellular carcinoma in chronic advanced liver disease. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.CD013362
3. Tajbakhsh N, Jeyaseelan L, Li Q et al (2020) Embracing imperfect datasets: a review of deep learning solutions for medical image segmentation. Med Image Anal 63:101693. https://doi.org/10.1016/j.media.2020.101693
4. Pandey SK, Janghel RR (2019) Recent deep learning techniques, challenges and its applications for medical healthcare system: a review. Neural Process Lett 50:1907–1935. https://doi.org/10.1007/s11063-018-09976-2
5. Emerson Nithiyaraj E, Arivazhagan S (2020) Survey on recent works in computed tomography based computer ‑ aided diagnosis of liver using deep learning techniques. Inter J Innov Sci Res Technol 5(7):173–181. https://doi.org/10.38124/IJISRT20JUL058
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