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Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection
المؤلفون المشاركون
Huang, Lianfen
Weng, Minghui
Shuai, Haitao
Huang, Yue
Sun, Jianjun
Gao, Fenglian
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-08-18
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Automatic liver segmentation not only plays an important role in the analysis of liver disease, but also reduces the cost and humanity’s impact in segmentation.
In addition, liver segmentation is a very challenging task due to countless anatomical variations and technical difficulties.
Many methods have been designed to overcome these challenges, but these methods still need to be improved to obtain the desired segmentation precision.
In this paper, a fast algorithm is proposed for liver extraction from CT images with single-block linear detection.
The proposed method does not require iteration; thus, the computational time and complexity are decreased enormously.
In addition, the initialization is not crucial in the algorithm, so the algorithm’s robustness and specificity are improved.
The experimental evaluation of the proposed method revealed effective segmentation in normal and abnormal (liver hemangioma and liver cancer) abdominal CT images.
The average sensitivity, accuracy, and specificity for liver cancer are 96.59%, 98.65%, and 99.03%, respectively.
The results of image segmentation approximate the manual segmentation results by the technical doctor.
Moreover, our method shows superior flexibility to newly published method with comparable performance.
The advantage of our method is verified with experimental results, which is described in detail.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Huang, Lianfen& Weng, Minghui& Shuai, Haitao& Huang, Yue& Sun, Jianjun& Gao, Fenglian. 2016. Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection. BioMed Research International،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099301
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Huang, Lianfen…[et al.]. Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection. BioMed Research International No. 2016 (2016), pp.1-11.
https://search.emarefa.net/detail/BIM-1099301
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Huang, Lianfen& Weng, Minghui& Shuai, Haitao& Huang, Yue& Sun, Jianjun& Gao, Fenglian. Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099301
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1099301
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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