Abstract:
:Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI) image which contains the liver tumor region in the T1-weighted MR image series was extracted by using seed points. The noise in this ROI image was reduced and the boundaries were enhanced. A 3D fast marching algorithm was applied to generate the initial labeled regions which are considered as teacher regions. A single hidden layer feedforward neural network (SLFN), which was trained by a noniterative algorithm, was employed to classify the unlabeled voxels. Finally, the postprocessing stage was applied to extract and refine the liver tumor boundaries. The liver tumors determined by our scheme were compared with those manually traced by a radiologist, used as the "ground truth." Results. The study was evaluated on two datasets of 25 tumors from 16 patients. The proposed scheme obtained the mean volumetric overlap error of 27.43% and the mean percentage volume error of 15.73%. The mean of the average surface distance, the root mean square surface distance, and the maximal surface distance were 0.58 mm, 1.20 mm, and 6.29 mm, respectively.
journal_name
Biomed Res Intjournal_title
BioMed research internationalauthors
Le TN,Bao PT,Huynh HTdoi
10.1155/2016/3219068subject
Has Abstractpub_date
2016-01-01 00:00:00pages
3219068eissn
2314-6133issn
2314-6141journal_volume
2016pub_type
杂志文章abstract::One of the most common complications of diabetes mellitus is diabetic neuropathy. It may be provoked by metabolic and/or vascular factors, and depending on duration of disease, various layers of nerve may be affected. Our aim was to investigate influence of diabetes on the epineurial, perineurial, and endoneurial conn...
journal_title:BioMed research international
pub_type: 杂志文章
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journal_title:BioMed research international
pub_type: 杂志文章
doi:10.1155/2016/8065765
更新日期:2016-01-01 00:00:00
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journal_title:BioMed research international
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journal_title:BioMed research international
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journal_title:BioMed research international
pub_type: 杂志文章,评审
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pub_type: 杂志文章,评审
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pub_type: 杂志文章
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pub_type: 杂志文章,评审
doi:10.1155/2013/202905
更新日期:2013-01-01 00:00:00
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journal_title:BioMed research international
pub_type: 杂志文章
doi:10.1155/2019/5280514
更新日期:2019-03-28 00:00:00
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pub_type: 杂志文章
doi:10.1155/2016/7627358
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journal_title:BioMed research international
pub_type: 杂志文章,meta分析
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pub_type: 杂志文章,评审
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pub_type: 杂志文章,评审
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