A Review of Advancements and Challenges in Liver Segmentation

被引：1
作者：
Wei, Di [1 ]
Jiang, Yundan [1 ]
Zhou, Xuhui [1 ]
Wu, Di [1 ]
Feng, Xiaorong [1 ]
机构：
[1] Sun Yat Sen Univ, Affiliated Hosp 8, Dept Radiol, 3025 Middle Shennan Rd, Shenzhen 518033, Peoples R China
来源：
JOURNAL OF IMAGING | 2024年 / 10卷 / 08期
关键词：
liver segmentation; medical imaging; deep learning; convolutional neural networks; fully; convolutional networks; U-Net; automated segmentation; CT;
D O I：
10.3390/jimaging10080202
中图分类号：
TB8 [摄影技术];
学科分类号：
0804 ;
摘要：
Liver segmentation technologies play vital roles in clinical diagnosis, disease monitoring, and surgical planning due to the complex anatomical structure and physiological functions of the liver. This paper provides a comprehensive review of the developments, challenges, and future directions in liver segmentation technology. We systematically analyzed high-quality research published between 2014 and 2024, focusing on liver segmentation methods, public datasets, and evaluation metrics. This review highlights the transition from manual to semi-automatic and fully automatic segmentation methods, describes the capabilities and limitations of available technologies, and provides future outlooks.
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页数：15
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共 45 条
  • [1] Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer
    Ahn, Sang Hee
    Yeo, Adam Unjin
    Kim, Kwang Hyeon
    Kim, Chankyu
    Goh, Youngmoon
    Cho, Shinhaeng
    Lee, Se Byeong
    Lim, Young Kyung
    Kim, Haksoo
    Shin, Dongho
    Kim, Taeyoon
    Kim, Tae Hyun
    Youn, Sang Hee
    Oh, Eun Sang
    Jeong, Jong Hwi
    [J]. RADIATION ONCOLOGY, 2019, 14 (01) : 1 - 13
  • [2] Deep Learning Algorithm for Automated Segmentation and Volume Measurement of the Liver and Spleen Using Portal Venous Phase Computed Tomography Images
    Ahn, Yura
    Yoon, Jee Seok
    Lee, Seung Soo
    Suk, Heung-Il
    Son, Jung Hee
    Sung, Yu Sub
    Lee, Yedaun
    Kang, Bo-Kyeong
    Kim, Ho Sung
    [J]. KOREAN JOURNAL OF RADIOLOGY, 2020, 21 (08) : 987 - 997
  • [3] Survey on Liver Tumour Resection Planning System: Steps, Techniques, and Parameters
    Alirr, Omar Ibrahim
    Abd Rahni, Ashrani Aizzuddin
    [J]. JOURNAL OF DIGITAL IMAGING, 2020, 33 (02) : 304 - 323
  • [4] Recurrent residual U-Net for medical image segmentation
    Alom, Md Zahangir
    Yakopcic, Chris
    Hasan, Mahmudul
    Taha, Tarek M.
    Asari, Vijayan K.
    [J]. JOURNAL OF MEDICAL IMAGING, 2019, 6 (01)
  • [5] Ansari MY, 2022, BMC MED IMAGING, V22, DOI 10.1186/s12880-022-00825-2
  • [6] Modified U-Net for liver cancer segmentation from computed tomography images with a new class balancing method
    Yodit Abebe Ayalew
    Kinde Anlay Fante
    Mohammed Aliy Mohammed
    [J]. BMC Biomedical Engineering, 3 (1):
  • [7] SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
    Badrinarayanan, Vijay
    Kendall, Alex
    Cipolla, Roberto
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2017, 39 (12) : 2481 - 2495
  • [8] Artificial intelligence, machine learning, and deep learning in liver transplantation
    Bhat, Mamatha
    Rabindranath, Madhumitha
    Chara, Beatriz Sordi
    Simonetto, Douglas A.
    [J]. JOURNAL OF HEPATOLOGY, 2023, 78 (06) : 1216 - 1233
  • [9] Bilic P., LiTS (Liver Tumor Segmentation Challenge)
  • [10] The Liver Tumor Segmentation Benchmark (LiTS)
    Bilic, Patrick
    Christ, Patrick
    Li, Hongwei Bran
    Vorontsov, Eugene
    Ben-Cohen, Avi
    Kaissis, Georgios
    Szeskin, Adi
    Jacobs, Colin
    Mamani, Gabriel Efrain Humpire
    Chartrand, Gabriel
    Lohoefer, Fabian
    Holch, Julian Walter
    Sommer, Wieland
    Hofmann, Felix
    Hostettler, Alexandre
    Lev-Cohain, Naama
    Drozdzal, Michal
    Amitai, Michal Marianne
    Vivanti, Refael
    Sosna, Jacob
    Ezhov, Ivan
    Sekuboyina, Anjany
    Navarro, Fernando
    Kofler, Florian
    Paetzold, Johannes C.
    Shit, Suprosanna
    Hu, Xiaobin
    Lipkova, Jana
    Rempfler, Markus
    Piraud, Marie
    Kirschke, Jan
    Wiestler, Benedikt
    Zhang, Zhiheng
    Huelsemeyer, Christian
    Beetz, Marcel
    Ettlinger, Florian
    Antonelli, Michela
    Bae, Woong
    Bellver, Miriam
    Bi, Lei
    Chen, Hao
    Chlebus, Grzegorz
    Dam, Erik B.
    Dou, Qi
    Fu, Chi-Wing
    Georgescu, Bogdan
    Giro-I-Nieto, Xavier
    Gruen, Felix
    Han, Xu
    Heng, Pheng-Ann
    [J]. MEDICAL IMAGE ANALYSIS, 2023, 84
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