Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2016/01/01
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Journal
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Indian UGC (journal)
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Refrences22
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Citations7
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Lianfen Huang Xiamen University, Xiamen, Fujian 361005, China ORCID
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Minghui Weng Xiamen University, Xiamen, Fujian 361005, China ORCID
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Haitao Shuai Department of Radiology, The 476th Clinic Section, Fuzhou General Hospital of the PLA, Fuzhou, Fujian 350002, China ORCID
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Yue Huang Xiamen University, Xiamen, Fujian 361005, China ORCID
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Jianjun Sun Department of Radiology, The 476th Clinic Section, Fuzhou General Hospital of the PLA, Fuzhou, Fujian 350002, China ORCID
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Fenglian Gao Xiamen University, Xiamen, Fujian 361005, China ORCID
Abstract
Cite
Huang, Lianfen, et al. “Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection”. BioMed Research International, vol. 2016, 2016, pp. 1-11, https://doi.org/10.1155/2016/9420148.
Huang, L., Weng, M., Shuai, H., Huang, Y., Sun, J., & Gao, F. (2016). Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection. BioMed Research International, 2016, 1-11. https://doi.org/10.1155/2016/9420148
Huang L, Weng M, Shuai H, Huang Y, Sun J, Gao F. Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection. BioMed Research International. 2016;2016:1-11.
Journal Categories
Medicine
Medicine (General)
Technology
Chemical technology
Biotechnology
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Neural network based texture analysis of CT images for fatty and cirrhosis liver classification | Applied Soft Computing |
| 24 | 2015 |
| Neural network based texture analysis of CT images for fatty and cirrhosis liver classification | Chinese Journal of Computers | 2015 | ||
| Neural network based texture analysis of CT images for fatty and cirrhosis liver classification | 2014 | |||
| Liver Segmentation from CT Image Using Fuzzy Clustering and Level Set | Journal of Signal and Information Processing | 2 | 2013 | |
| Automatic liver and lesion segmentation: a primary step in diagnosis of liver diseases | Signal, Image and Video Processing |
| 37 | 2011 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Retinal Vessel Segmentation in Medical Diagnosis using Multi-scale Attention Generative Adversarial Networks | Mobile Networks and Applications |
| 2023 | |
Recent advances in computerized imaging and its vital roles in liver disease diagnosis, preoperative planning, and interventional liver surgery: A review | World Journal of Gastrointestinal Surgery |
| 2023 | |
| The application of artificial intelligence in hepatology: A systematic review | Digestive and Liver Disease |
| 12 | 2022 |
| Adaptable volumetric liver segmentation model for CT images using region-based features and convolutional neural network | Neurocomputing |
| 6 | 2022 |
Automatic Liver Segmentation in CT Images with Enhanced GAN and Mask Region-Based CNN Architectures | BioMed Research International |
| 10 | 2021 |
Citations Analysis
The category
Medicine: Medicine (General) 4
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Automatic Liver Segmentation in CT Images with Enhanced GAN and Mask Region-Based CNN Architectures and was published in 2021. The most recent citation comes from a 2023 study titled Recent advances in computerized imaging and its vital roles in liver disease diagnosis, preoperative planning, and interventional liver surgery: A review. This article reached its peak citation in 2021, with 3 citations. It has been cited in 7 different journals, 14% of which are open access. Among related journals, the World Journal of Gastrointestinal Surgery cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.