Segmentation and Diagnosis of Papillary Thyroid Carcinomas Based on Generalized Clustering Algorithm in Ultrasound Elastography
Papillary thyroid carcinomas (PTC) are the most common type of thyroid malignant tumors. Existing methods for clustering high-noise ultrasound images tend to degrade the clustering performance. In order to realize accurate segmentation of thyroid nodule in noisy environment, this paper proposes an i...
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| Published in: | Journal of medical systems Vol. 44; no. 1; pp. 13 - 8 |
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| Format: | Journal Article |
| Language: | English |
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Springer US
01.01.2020
Springer Nature B.V |
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| ISSN: | 0148-5598, 1573-689X, 1573-689X |
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| Abstract | Papillary thyroid carcinomas (PTC) are the most common type of thyroid malignant tumors. Existing methods for clustering high-noise ultrasound images tend to degrade the clustering performance. In order to realize accurate segmentation of thyroid nodule in noisy environment, this paper proposes an improved segmentation algorithm based on adaptive fast generalized clustering. Firstly, the parameter balance factor is adaptively determined according to the noise probability of non-local pixels so as to reflect the spatial structure information in the image more accurately. Then, the balance factor is used to effectively combine the linear weighted filtered image in the AFGC algorithm so as to create the adaptive filtered image. Since the filtering degree depends on the probability whether the pixel is noise in the image, the dynamic noise suppression performance of the proposed method can be greatly improved. A large number of qualitative and quantitative experimental results show that the proposed generalized clustering algorithm can obtain more accurate results when clustering images with high noise. It is suitable for intelligent diagnosis of papillary thyroid convolution in clinical examination. |
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| AbstractList | Papillary thyroid carcinomas (PTC) are the most common type of thyroid malignant tumors. Existing methods for clustering high-noise ultrasound images tend to degrade the clustering performance. In order to realize accurate segmentation of thyroid nodule in noisy environment, this paper proposes an improved segmentation algorithm based on adaptive fast generalized clustering. Firstly, the parameter balance factor is adaptively determined according to the noise probability of non-local pixels so as to reflect the spatial structure information in the image more accurately. Then, the balance factor is used to effectively combine the linear weighted filtered image in the AFGC algorithm so as to create the adaptive filtered image. Since the filtering degree depends on the probability whether the pixel is noise in the image, the dynamic noise suppression performance of the proposed method can be greatly improved. A large number of qualitative and quantitative experimental results show that the proposed generalized clustering algorithm can obtain more accurate results when clustering images with high noise. It is suitable for intelligent diagnosis of papillary thyroid convolution in clinical examination. Papillary thyroid carcinomas (PTC) are the most common type of thyroid malignant tumors. Existing methods for clustering high-noise ultrasound images tend to degrade the clustering performance. In order to realize accurate segmentation of thyroid nodule in noisy environment, this paper proposes an improved segmentation algorithm based on adaptive fast generalized clustering. Firstly, the parameter balance factor is adaptively determined according to the noise probability of non-local pixels so as to reflect the spatial structure information in the image more accurately. Then, the balance factor is used to effectively combine the linear weighted filtered image in the AFGC algorithm so as to create the adaptive filtered image. Since the filtering degree depends on the probability whether the pixel is noise in the image, the dynamic noise suppression performance of the proposed method can be greatly improved. A large number of qualitative and quantitative experimental results show that the proposed generalized clustering algorithm can obtain more accurate results when clustering images with high noise. It is suitable for intelligent diagnosis of papillary thyroid convolution in clinical examination.Papillary thyroid carcinomas (PTC) are the most common type of thyroid malignant tumors. Existing methods for clustering high-noise ultrasound images tend to degrade the clustering performance. In order to realize accurate segmentation of thyroid nodule in noisy environment, this paper proposes an improved segmentation algorithm based on adaptive fast generalized clustering. Firstly, the parameter balance factor is adaptively determined according to the noise probability of non-local pixels so as to reflect the spatial structure information in the image more accurately. Then, the balance factor is used to effectively combine the linear weighted filtered image in the AFGC algorithm so as to create the adaptive filtered image. Since the filtering degree depends on the probability whether the pixel is noise in the image, the dynamic noise suppression performance of the proposed method can be greatly improved. A large number of qualitative and quantitative experimental results show that the proposed generalized clustering algorithm can obtain more accurate results when clustering images with high noise. It is suitable for intelligent diagnosis of papillary thyroid convolution in clinical examination. |
| ArticleNumber | 13 |
| Author | Huang, Weiqiang |
| Author_xml | – sequence: 1 givenname: Weiqiang surname: Huang fullname: Huang, Weiqiang email: jxjszhhog@163.com organization: The first people’s hospital of Jinshan |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31811492$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1016_j_engappai_2020_104064 crossref_primary_10_3390_math9222970 crossref_primary_10_1155_2021_6115040 crossref_primary_10_3389_fonc_2023_1197447 crossref_primary_10_1007_s12602_025_10471_z |
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| DOI | 10.1007/s10916-019-1462-7 |
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| Keywords | Diagnosis Spatial structure Papillary thyroid carcinomas Object segmentation Balance factor Generalized clustering |
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| Snippet | Papillary thyroid carcinomas (PTC) are the most common type of thyroid malignant tumors. Existing methods for clustering high-noise ultrasound images tend to... |
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| SubjectTerms | Adaptive algorithms Adaptive filters Algorithms Clustering Convolution Diagnosis Distributed Analytics and Deep Learning in Health Care Health Informatics Health Sciences Image & Signal Processing Image filters Image processing Image segmentation Medical diagnosis Medicine Medicine & Public Health Noise Papillary thyroid carcinoma Pixels Statistics for Life Sciences Thyroid Thyroid cancer Thyroid gland Tumors Ultrasonic imaging Ultrasound |
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| Title | Segmentation and Diagnosis of Papillary Thyroid Carcinomas Based on Generalized Clustering Algorithm in Ultrasound Elastography |
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