An automatic method for segmentation of liver lesions in computed tomography images using deep neural networks

Author:

Araújo José Denes Lima,da Cruz Luana Batista,Ferreira Jonnison Lima,da Silva Neto Otilio Paulo,Silva Aristófanes Corrêa,de Paiva Anselmo Cardoso,Gattass Marcelo

Funder

Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference46 articles.

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2. Abdel-Misih, S.R.Z., & Bloomston, M. (2010). Liver anatomy. Surgical Clinics of North America, 90, 643–653. URL:https://www.sciencedirect.com/science/article/pii/S0039610910000526. doi: 10.1016/j.suc.2010.04.017. Liver Surgery: From Basics to Robotics.

3. Agarwal, S., Terrail, J.O.D., & Jurie, F. (2018). Recent advances in object detection in the age of deep convolutional neural networks. ArXiv, abs/1809.03193.

4. Liver tumor segmentation based on multi-scale candidate generation and fractal residual network;Bai;IEEE Access,2019

5. Active contours and their utilization at image segmentation;Bakoš,2007

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