Method for dividing the static parameters of nailfold capillary: Improving measurement accuracy Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.21203/rs.3.rs-7009260/v1
Improving the accuracy of nailfold capillary static parameter measurements is currently a popular area of research. Currently, the division of nailfold capillary static parameter areas is usually based on the experience of the clinical practitioner, and those with less experience exhibit high error rates. This study aims to reduce the error rate by developing an automated method for measuring the static parameters of nailfold capillary. This study used digital image processing combined with deep learning to accurately delineate the parameter areas that correspond to the apical, arterial, and venous branches. Subsequently, the calculated pipe diameters of the three static parameters of the apical, arterial, and venous limbs were compared with the manually measured pipe diameters. Experimental results demonstrate that the root mean square error (RMSE) (µm) of the three static parameter measurements of the apical, arterial limb, and venous limb compared with the manually measured values are 0.614, 0.71, and 0.686, respectively. The accuracy of the proposed method is 91%. Additionally, we calculated the P values of the algorithmic and manual measurements to be P < 0.001 and found that the difference in the measurements of the proposed algorithm is statistically significant. The proposed method demonstrates high accuracy in the measurement of the static parameters of nailfold capillary, providing an effective solution for the time-consuming process and high labor costs of measuring the static parameters of nailfold capillary.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-7009260/v1
- https://www.researchsquare.com/article/rs-7009260/latest.pdf
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4412173224Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-7009260/v1Digital Object Identifier
- Title
-
Method for dividing the static parameters of nailfold capillary: Improving measurement accuracyWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-07-10Full publication date if available
- Authors
-
Bin Zhou, Jiawei He, Peiqing Guo, Jianan Lin, Feng Shou, Hao Yin, Qirui Sun, Hongjun Zhou, Yanxiong Wu, Fanxin ZengList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-7009260/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-7009260/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-7009260/latest.pdfDirect OA link when available
- Concepts
-
Capillary action, Computer science, Statistics, Mathematics, Materials science, Composite materialTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.rates. | 44 |
| abstract_inverted_index.reduce | 49 |
| abstract_inverted_index.square | 123 |
| abstract_inverted_index.static | 7, 23, 61, 99, 130, 204, 224 |
| abstract_inverted_index.values | 146, 166 |
| abstract_inverted_index.venous | 89, 106, 139 |
| abstract_inverted_index.apical, | 86, 103, 135 |
| abstract_inverted_index.digital | 69 |
| abstract_inverted_index.exhibit | 41 |
| abstract_inverted_index.popular | 13 |
| abstract_inverted_index.process | 216 |
| abstract_inverted_index.results | 117 |
| abstract_inverted_index.usually | 27 |
| abstract_inverted_index.accuracy | 3, 154, 198 |
| abstract_inverted_index.arterial | 136 |
| abstract_inverted_index.clinical | 34 |
| abstract_inverted_index.combined | 72 |
| abstract_inverted_index.compared | 109, 141 |
| abstract_inverted_index.division | 19 |
| abstract_inverted_index.learning | 75 |
| abstract_inverted_index.manually | 112, 144 |
| abstract_inverted_index.measured | 113, 145 |
| abstract_inverted_index.nailfold | 5, 21, 64, 207, 227 |
| abstract_inverted_index.proposed | 157, 188, 194 |
| abstract_inverted_index.solution | 212 |
| abstract_inverted_index.Improving | 1 |
| abstract_inverted_index.algorithm | 189 |
| abstract_inverted_index.arterial, | 87, 104 |
| abstract_inverted_index.automated | 56 |
| abstract_inverted_index.branches. | 90 |
| abstract_inverted_index.capillary | 6, 22 |
| abstract_inverted_index.currently | 11 |
| abstract_inverted_index.delineate | 78 |
| abstract_inverted_index.diameters | 95 |
| abstract_inverted_index.effective | 211 |
| abstract_inverted_index.measuring | 59, 222 |
| abstract_inverted_index.parameter | 8, 24, 80, 131 |
| abstract_inverted_index.providing | 209 |
| abstract_inverted_index.research. | 16 |
| abstract_inverted_index.Currently, | 17 |
| abstract_inverted_index.accurately | 77 |
| abstract_inverted_index.calculated | 93, 163 |
| abstract_inverted_index.capillary, | 208 |
| abstract_inverted_index.capillary. | 65, 228 |
| abstract_inverted_index.correspond | 83 |
| abstract_inverted_index.developing | 54 |
| abstract_inverted_index.diameters. | 115 |
| abstract_inverted_index.difference | 182 |
| abstract_inverted_index.experience | 31, 40 |
| abstract_inverted_index.parameters | 62, 100, 205, 225 |
| abstract_inverted_index.processing | 71 |
| abstract_inverted_index.algorithmic | 169 |
| abstract_inverted_index.demonstrate | 118 |
| abstract_inverted_index.measurement | 201 |
| abstract_inverted_index.Experimental | 116 |
| abstract_inverted_index.demonstrates | 196 |
| abstract_inverted_index.measurements | 9, 132, 172, 185 |
| abstract_inverted_index.significant. | 192 |
| abstract_inverted_index.Additionally, | 161 |
| abstract_inverted_index.Subsequently, | 91 |
| abstract_inverted_index.practitioner, | 35 |
| abstract_inverted_index.respectively. | 152 |
| abstract_inverted_index.statistically | 191 |
| abstract_inverted_index.time-consuming | 215 |
| abstract_inverted_index.<title>Abstract</title> | 0 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 10 |
| citation_normalized_percentile.value | 0.20787526 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |