AdvYOLO: Advanced YOLOv8 Application for Bone Pathology Localization and Classification in Wrist X-ray Images Article Swipe
Rongxiang Wang
,
Jingwen Zhao
,
Xiang Liu
,
Xian Tang
,
Yunyu Shi
,
Lina Wei
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4051336/v1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4051336/v1
In the field of pediatric orthopedics, accurate and timely identification of wrist fractures is vital for effective treatment and recovery. Fractures significantly affect daily activities and can lead to long-term health issues. Especially in areas with limited medical resources, or for doctors with less experience, interpreting X-ray images accurately is challenging. This paper introduces the AdvYOLO algorithm, an enhanced version of YOLOv8, trained on the GRAZPEDWRI-DX dataset to diagnose wrist bone pathologies. The integration of the Dilation-wise Residual (DWR) and Large Separable Kernel Attention (LSKA) modules is critical for improving feature extraction and classification, as they allow more effective processing of complex patterns in X-ray images, leading to more accurate diagnostics. The mAP 50 value of AdvYOLO improved from 63.8\% to 68.7\%, achieving state-of-the-art performance in wrist detection. Additionally, the paper presents BoneVisionAI, a tool to assist doctors, particularly those with less experience, in accurately interpreting children's wrist X-rays, aiming to reduce diagnostic errors in the healthcare sector.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-4051336/v1
- https://www.researchsquare.com/article/rs-4051336/latest.pdf
- OA Status
- green
- Cited By
- 1
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4393319419
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4393319419Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-4051336/v1Digital Object Identifier
- Title
-
AdvYOLO: Advanced YOLOv8 Application for Bone Pathology Localization and Classification in Wrist X-ray ImagesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-29Full publication date if available
- Authors
-
Rongxiang Wang, Jingwen Zhao, Xiang Liu, Xian Tang, Yunyu Shi, Lina WeiList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-4051336/v1Publisher landing page
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https://www.researchsquare.com/article/rs-4051336/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-4051336/latest.pdfDirect OA link when available
- Concepts
-
Wrist, Medicine, Computer science, Orthodontics, AnatomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- References (count)
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43Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.affect | 23 |
| abstract_inverted_index.aiming | 150 |
| abstract_inverted_index.assist | 137 |
| abstract_inverted_index.errors | 154 |
| abstract_inverted_index.health | 31 |
| abstract_inverted_index.images | 48 |
| abstract_inverted_index.reduce | 152 |
| abstract_inverted_index.timely | 9 |
| abstract_inverted_index.68.7\%, | 122 |
| abstract_inverted_index.AdvYOLO | 56, 117 |
| abstract_inverted_index.X-rays, | 149 |
| abstract_inverted_index.YOLOv8, | 62 |
| abstract_inverted_index.complex | 102 |
| abstract_inverted_index.dataset | 67 |
| abstract_inverted_index.doctors | 42 |
| abstract_inverted_index.feature | 91 |
| abstract_inverted_index.images, | 106 |
| abstract_inverted_index.issues. | 32 |
| abstract_inverted_index.leading | 107 |
| abstract_inverted_index.limited | 37 |
| abstract_inverted_index.medical | 38 |
| abstract_inverted_index.modules | 86 |
| abstract_inverted_index.sector. | 158 |
| abstract_inverted_index.trained | 63 |
| abstract_inverted_index.version | 60 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Residual | 78 |
| abstract_inverted_index.accurate | 7, 110 |
| abstract_inverted_index.critical | 88 |
| abstract_inverted_index.diagnose | 69 |
| abstract_inverted_index.doctors, | 138 |
| abstract_inverted_index.enhanced | 59 |
| abstract_inverted_index.improved | 118 |
| abstract_inverted_index.patterns | 103 |
| abstract_inverted_index.presents | 132 |
| abstract_inverted_index.Attention | 84 |
| abstract_inverted_index.Fractures | 21 |
| abstract_inverted_index.Separable | 82 |
| abstract_inverted_index.achieving | 123 |
| abstract_inverted_index.effective | 17, 99 |
| abstract_inverted_index.fractures | 13 |
| abstract_inverted_index.improving | 90 |
| abstract_inverted_index.long-term | 30 |
| abstract_inverted_index.pediatric | 5 |
| abstract_inverted_index.recovery. | 20 |
| abstract_inverted_index.treatment | 18 |
| abstract_inverted_index.Especially | 33 |
| abstract_inverted_index.accurately | 49, 145 |
| abstract_inverted_index.activities | 25 |
| abstract_inverted_index.algorithm, | 57 |
| abstract_inverted_index.children's | 147 |
| abstract_inverted_index.detection. | 128 |
| abstract_inverted_index.diagnostic | 153 |
| abstract_inverted_index.extraction | 92 |
| abstract_inverted_index.healthcare | 157 |
| abstract_inverted_index.introduces | 54 |
| abstract_inverted_index.processing | 100 |
| abstract_inverted_index.resources, | 39 |
| abstract_inverted_index.experience, | 45, 143 |
| abstract_inverted_index.integration | 74 |
| abstract_inverted_index.performance | 125 |
| abstract_inverted_index.challenging. | 51 |
| abstract_inverted_index.diagnostics. | 111 |
| abstract_inverted_index.interpreting | 46, 146 |
| abstract_inverted_index.orthopedics, | 6 |
| abstract_inverted_index.particularly | 139 |
| abstract_inverted_index.pathologies. | 72 |
| abstract_inverted_index.Additionally, | 129 |
| abstract_inverted_index.BoneVisionAI, | 133 |
| abstract_inverted_index.Dilation-wise | 77 |
| abstract_inverted_index.GRAZPEDWRI-DX | 66 |
| abstract_inverted_index.significantly | 22 |
| abstract_inverted_index.identification | 10 |
| abstract_inverted_index.classification, | 94 |
| abstract_inverted_index.state-of-the-art | 124 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5019548473 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I141962983 |
| citation_normalized_percentile.value | 0.47917341 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |