Structure-Enhanced Attentive Learning For Spine Segmentation From Ultrasound Volume Projection Images Article Swipe
Rui Zhao
,
Zixun Huang
,
Tianshan Liu
,
F.H.F. Leung
,
Sai Ho Ling
,
Deyou Yang
,
Timothy Tin‐Yan Lee
,
Daniel Pak-Kong Lun
,
Yong‐Ping Zheng
,
Kin‐Man Lam
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/icassp39728.2021.9414658
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/icassp39728.2021.9414658
Automatic spine segmentation, based on ultrasound volume projection imaging (VPI), is of great value in clinical applications to diagnose scoliosis in teenagers. In this paper, we propose a novel framework to improve the segmentation accuracy on spine images via structure-enhanced attentive learning. Since the spine bones contain strong prior knowledge of their shapes and positions in ultrasound VPI images, we propose to encode this information into the semantic representations in an attentive manner. We first revisit the self-attention mechanism in representation learning, and then present a strategy to introduce the structural knowledge into the key representation in self-attention. By this means, the network explores both the contextual and structural information in the learned features, and consequently improves the segmentation accuracy. We conduct various experiments to demonstrate that our proposed method achieves promising performance on spine image segmentation, which shows great potential in clinical diagnosis.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/icassp39728.2021.9414658
- OA Status
- green
- Cited By
- 6
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3162447598
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3162447598Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/icassp39728.2021.9414658Digital Object Identifier
- Title
-
Structure-Enhanced Attentive Learning For Spine Segmentation From Ultrasound Volume Projection ImagesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-05-13Full publication date if available
- Authors
-
Rui Zhao, Zixun Huang, Tianshan Liu, F.H.F. Leung, Sai Ho Ling, Deyou Yang, Timothy Tin‐Yan Lee, Daniel Pak-Kong Lun, Yong‐Ping Zheng, Kin‐Man LamList of authors in order
- Landing page
-
https://doi.org/10.1109/icassp39728.2021.9414658Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://ira.lib.polyu.edu.hk/bitstream/10397/94799/1/Zhao_Structure-Enhanced_Attentive_Learning.pdfDirect OA link when available
- Concepts
-
Segmentation, Computer science, Artificial intelligence, Representation (politics), Feature learning, Projection (relational algebra), Image segmentation, Computer vision, Artificial neural network, Deep learning, Pattern recognition (psychology), Algorithm, Politics, Law, Political scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2, 2023: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
33Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3162447598 |
|---|---|
| doi | https://doi.org/10.1109/icassp39728.2021.9414658 |
| ids.doi | https://doi.org/10.1109/icassp39728.2021.9414658 |
| ids.mag | 3162447598 |
| ids.openalex | https://openalex.org/W3162447598 |
| fwci | 0.46201149 |
| type | article |
| title | Structure-Enhanced Attentive Learning For Spine Segmentation From Ultrasound Volume Projection Images |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 1199 |
| biblio.first_page | 1195 |
| topics[0].id | https://openalex.org/T14510 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9991000294685364 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2204 |
| topics[0].subfield.display_name | Biomedical Engineering |
| topics[0].display_name | Medical Imaging and Analysis |
| topics[1].id | https://openalex.org/T11030 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9876000285148621 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2746 |
| topics[1].subfield.display_name | Surgery |
| topics[1].display_name | Scoliosis diagnosis and treatment |
| topics[2].id | https://openalex.org/T12740 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9724000096321106 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2204 |
| topics[2].subfield.display_name | Biomedical Engineering |
| topics[2].display_name | Gait Recognition and Analysis |
| funders[0].id | https://openalex.org/F4320307285 |
| funders[0].ror | https://ror.org/00jb20j87 |
| funders[0].display_name | Impact Fund |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C89600930 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8389459848403931 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1423946 |
| concepts[0].display_name | Segmentation |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.7606695890426636 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C154945302 |
| concepts[2].level | 1 |
| concepts[2].score | 0.734041690826416 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[2].display_name | Artificial intelligence |
| concepts[3].id | https://openalex.org/C2776359362 |
| concepts[3].level | 3 |
| concepts[3].score | 0.6136400103569031 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2145286 |
| concepts[3].display_name | Representation (politics) |
| concepts[4].id | https://openalex.org/C59404180 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5113665461540222 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q17013334 |
| concepts[4].display_name | Feature learning |
| concepts[5].id | https://openalex.org/C57493831 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5059632658958435 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q3134666 |
| concepts[5].display_name | Projection (relational algebra) |
| concepts[6].id | https://openalex.org/C124504099 |
| concepts[6].level | 3 |
| concepts[6].score | 0.49056190252304077 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q56933 |
| concepts[6].display_name | Image segmentation |
| concepts[7].id | https://openalex.org/C31972630 |
| concepts[7].level | 1 |
| concepts[7].score | 0.4845558702945709 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[7].display_name | Computer vision |
| concepts[8].id | https://openalex.org/C50644808 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4481017291545868 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[8].display_name | Artificial neural network |
| concepts[9].id | https://openalex.org/C108583219 |
| concepts[9].level | 2 |
| concepts[9].score | 0.4443667531013489 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q197536 |
| concepts[9].display_name | Deep learning |
| concepts[10].id | https://openalex.org/C153180895 |
| concepts[10].level | 2 |
| concepts[10].score | 0.423086941242218 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[10].display_name | Pattern recognition (psychology) |
| concepts[11].id | https://openalex.org/C11413529 |
| concepts[11].level | 1 |
| concepts[11].score | 0.06305825710296631 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[11].display_name | Algorithm |
| concepts[12].id | https://openalex.org/C94625758 |
| concepts[12].level | 2 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q7163 |
| concepts[12].display_name | Politics |
| concepts[13].id | https://openalex.org/C199539241 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q7748 |
| concepts[13].display_name | Law |
| concepts[14].id | https://openalex.org/C17744445 |
| concepts[14].level | 0 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q36442 |
| concepts[14].display_name | Political science |
| keywords[0].id | https://openalex.org/keywords/segmentation |
| keywords[0].score | 0.8389459848403931 |
| keywords[0].display_name | Segmentation |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.7606695890426636 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[2].score | 0.734041690826416 |
| keywords[2].display_name | Artificial intelligence |
| keywords[3].id | https://openalex.org/keywords/representation |
| keywords[3].score | 0.6136400103569031 |
| keywords[3].display_name | Representation (politics) |
| keywords[4].id | https://openalex.org/keywords/feature-learning |
| keywords[4].score | 0.5113665461540222 |
| keywords[4].display_name | Feature learning |
| keywords[5].id | https://openalex.org/keywords/projection |
| keywords[5].score | 0.5059632658958435 |
| keywords[5].display_name | Projection (relational algebra) |
| keywords[6].id | https://openalex.org/keywords/image-segmentation |
| keywords[6].score | 0.49056190252304077 |
| keywords[6].display_name | Image segmentation |
| keywords[7].id | https://openalex.org/keywords/computer-vision |
| keywords[7].score | 0.4845558702945709 |
| keywords[7].display_name | Computer vision |
| keywords[8].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[8].score | 0.4481017291545868 |
| keywords[8].display_name | Artificial neural network |
| keywords[9].id | https://openalex.org/keywords/deep-learning |
| keywords[9].score | 0.4443667531013489 |
| keywords[9].display_name | Deep learning |
| keywords[10].id | https://openalex.org/keywords/pattern-recognition |
| keywords[10].score | 0.423086941242218 |
| keywords[10].display_name | Pattern recognition (psychology) |
| keywords[11].id | https://openalex.org/keywords/algorithm |
| keywords[11].score | 0.06305825710296631 |
| keywords[11].display_name | Algorithm |
| language | en |
| locations[0].id | doi:10.1109/icassp39728.2021.9414658 |
| locations[0].is_oa | False |
| locations[0].source | |
| locations[0].license | |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | proceedings-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
| locations[0].landing_page_url | https://doi.org/10.1109/icassp39728.2021.9414658 |
| locations[1].id | pmh:oai:ira.lib.polyu.edu.hk:10397/94799 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400205 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PolyU Institutional Research Archive (Hong Kong Polytechnic University) |
| locations[1].source.host_organization | https://openalex.org/I14243506 |
| locations[1].source.host_organization_name | Hong Kong Polytechnic University |
| locations[1].source.host_organization_lineage | https://openalex.org/I14243506 |
| locations[1].license | |
| locations[1].pdf_url | http://ira.lib.polyu.edu.hk/bitstream/10397/94799/1/Zhao_Structure-Enhanced_Attentive_Learning.pdf |
| locations[1].version | submittedVersion |
| locations[1].raw_type | Conference Paper |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | http://hdl.handle.net/10397/94799 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5102019205 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-2733-3617 |
| authorships[0].author.display_name | Rui Zhao |
| authorships[0].countries | HK |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[0].institutions[0].id | https://openalex.org/I14243506 |
| authorships[0].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[0].institutions[0].country_code | HK |
| authorships[0].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Rui Zhao |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[1].author.id | https://openalex.org/A5089406697 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-0930-4276 |
| authorships[1].author.display_name | Zixun Huang |
| authorships[1].countries | HK |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[1].institutions[0].id | https://openalex.org/I14243506 |
| authorships[1].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[1].institutions[0].country_code | HK |
| authorships[1].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Zixun Huang |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[2].author.id | https://openalex.org/A5011105024 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-3831-8893 |
| authorships[2].author.display_name | Tianshan Liu |
| authorships[2].countries | HK |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[2].institutions[0].id | https://openalex.org/I14243506 |
| authorships[2].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[2].institutions[0].country_code | HK |
| authorships[2].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Tianshan Liu |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[3].author.id | https://openalex.org/A5056524805 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-3921-7074 |
| authorships[3].author.display_name | F.H.F. Leung |
| authorships[3].countries | HK |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[3].institutions[0].id | https://openalex.org/I14243506 |
| authorships[3].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[3].institutions[0].country_code | HK |
| authorships[3].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Frank H. F. Leung |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[4].author.id | https://openalex.org/A5079852457 |
| authorships[4].author.orcid | https://orcid.org/0000-0003-0849-5098 |
| authorships[4].author.display_name | Sai Ho Ling |
| authorships[4].countries | AU |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I114017466 |
| authorships[4].affiliations[0].raw_affiliation_string | School of Biomedical Engineering, University of Technology Sydney, NSW, Australia |
| authorships[4].institutions[0].id | https://openalex.org/I114017466 |
| authorships[4].institutions[0].ror | https://ror.org/03f0f6041 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I114017466 |
| authorships[4].institutions[0].country_code | AU |
| authorships[4].institutions[0].display_name | University of Technology Sydney |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Sai Ho Ling |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | School of Biomedical Engineering, University of Technology Sydney, NSW, Australia |
| authorships[5].author.id | https://openalex.org/A5016957995 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-6230-6473 |
| authorships[5].author.display_name | Deyou Yang |
| authorships[5].countries | HK |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[5].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[5].institutions[0].id | https://openalex.org/I14243506 |
| authorships[5].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[5].institutions[0].country_code | HK |
| authorships[5].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | De Yang |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[6].author.id | https://openalex.org/A5010826473 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-4194-4345 |
| authorships[6].author.display_name | Timothy Tin‐Yan Lee |
| authorships[6].countries | HK |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[6].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[6].institutions[0].id | https://openalex.org/I14243506 |
| authorships[6].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[6].institutions[0].country_code | HK |
| authorships[6].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Timothy Tin-Yan Lee |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[7].author.id | https://openalex.org/A5045479823 |
| authorships[7].author.orcid | https://orcid.org/0000-0003-3891-1363 |
| authorships[7].author.display_name | Daniel Pak-Kong Lun |
| authorships[7].countries | HK |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[7].affiliations[0].raw_affiliation_string | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[7].institutions[0].id | https://openalex.org/I14243506 |
| authorships[7].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[7].institutions[0].country_code | HK |
| authorships[7].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Daniel P.K. Lun |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[8].author.id | https://openalex.org/A5100673553 |
| authorships[8].author.orcid | https://orcid.org/0000-0002-3407-9226 |
| authorships[8].author.display_name | Yong‐Ping Zheng |
| authorships[8].countries | HK |
| authorships[8].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[8].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[8].institutions[0].id | https://openalex.org/I14243506 |
| authorships[8].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[8].institutions[0].type | education |
| authorships[8].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[8].institutions[0].country_code | HK |
| authorships[8].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Yong-Ping Zheng |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[9].author.id | https://openalex.org/A5019678322 |
| authorships[9].author.orcid | https://orcid.org/0000-0002-0422-8454 |
| authorships[9].author.display_name | Kin‐Man Lam |
| authorships[9].countries | HK |
| authorships[9].affiliations[0].institution_ids | https://openalex.org/I14243506 |
| authorships[9].affiliations[0].raw_affiliation_string | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| authorships[9].institutions[0].id | https://openalex.org/I14243506 |
| authorships[9].institutions[0].ror | https://ror.org/0030zas98 |
| authorships[9].institutions[0].type | education |
| authorships[9].institutions[0].lineage | https://openalex.org/I14243506 |
| authorships[9].institutions[0].country_code | HK |
| authorships[9].institutions[0].display_name | Hong Kong Polytechnic University |
| authorships[9].author_position | last |
| authorships[9].raw_author_name | Kin-Man Lam |
| authorships[9].is_corresponding | False |
| authorships[9].raw_affiliation_strings | Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | http://ira.lib.polyu.edu.hk/bitstream/10397/94799/1/Zhao_Structure-Enhanced_Attentive_Learning.pdf |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Structure-Enhanced Attentive Learning For Spine Segmentation From Ultrasound Volume Projection Images |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T14510 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9991000294685364 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2204 |
| primary_topic.subfield.display_name | Biomedical Engineering |
| primary_topic.display_name | Medical Imaging and Analysis |
| related_works | https://openalex.org/W4375867731, https://openalex.org/W2611989081, https://openalex.org/W4230611425, https://openalex.org/W2731899572, https://openalex.org/W4304166257, https://openalex.org/W4294635752, https://openalex.org/W4315434538, https://openalex.org/W1522196789, https://openalex.org/W3048601286, https://openalex.org/W2965925734 |
| cited_by_count | 6 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 2 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 2 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:ira.lib.polyu.edu.hk:10397/94799 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400205 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | PolyU Institutional Research Archive (Hong Kong Polytechnic University) |
| best_oa_location.source.host_organization | https://openalex.org/I14243506 |
| best_oa_location.source.host_organization_name | Hong Kong Polytechnic University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I14243506 |
| best_oa_location.license | |
| best_oa_location.pdf_url | http://ira.lib.polyu.edu.hk/bitstream/10397/94799/1/Zhao_Structure-Enhanced_Attentive_Learning.pdf |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | Conference Paper |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://hdl.handle.net/10397/94799 |
| primary_location.id | doi:10.1109/icassp39728.2021.9414658 |
| primary_location.is_oa | False |
| primary_location.source | |
| primary_location.license | |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | proceedings-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
| primary_location.landing_page_url | https://doi.org/10.1109/icassp39728.2021.9414658 |
| publication_date | 2021-05-13 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W2914444914, https://openalex.org/W2989769843, https://openalex.org/W6770301750, https://openalex.org/W6766814535, https://openalex.org/W6776684981, https://openalex.org/W3034602892, https://openalex.org/W6756040250, https://openalex.org/W2910628332, https://openalex.org/W6726497184, https://openalex.org/W2959048247, https://openalex.org/W6639824700, https://openalex.org/W2963182609, https://openalex.org/W6775840997, https://openalex.org/W3028433770, https://openalex.org/W3092247414, https://openalex.org/W6779988263, https://openalex.org/W2009054260, https://openalex.org/W118778537, https://openalex.org/W1522301498, https://openalex.org/W2963091558, https://openalex.org/W2955058313, https://openalex.org/W2963263347, https://openalex.org/W3099986388, https://openalex.org/W2964121744, https://openalex.org/W3034045923, https://openalex.org/W3112508160, https://openalex.org/W3015324789, https://openalex.org/W3021293129, https://openalex.org/W2236297715, https://openalex.org/W1901129140, https://openalex.org/W2993235622, https://openalex.org/W2899771611, https://openalex.org/W2989968504 |
| referenced_works_count | 33 |
| abstract_inverted_index.a | 27, 85 |
| abstract_inverted_index.By | 98 |
| abstract_inverted_index.In | 22 |
| abstract_inverted_index.We | 73, 120 |
| abstract_inverted_index.an | 70 |
| abstract_inverted_index.in | 14, 20, 55, 69, 79, 96, 110, 141 |
| abstract_inverted_index.is | 10 |
| abstract_inverted_index.of | 11, 50 |
| abstract_inverted_index.on | 4, 35, 133 |
| abstract_inverted_index.to | 17, 30, 61, 87, 124 |
| abstract_inverted_index.we | 25, 59 |
| abstract_inverted_index.VPI | 57 |
| abstract_inverted_index.and | 53, 82, 107, 114 |
| abstract_inverted_index.key | 94 |
| abstract_inverted_index.our | 127 |
| abstract_inverted_index.the | 32, 43, 66, 76, 89, 93, 101, 105, 111, 117 |
| abstract_inverted_index.via | 38 |
| abstract_inverted_index.both | 104 |
| abstract_inverted_index.into | 65, 92 |
| abstract_inverted_index.that | 126 |
| abstract_inverted_index.then | 83 |
| abstract_inverted_index.this | 23, 63, 99 |
| abstract_inverted_index.Since | 42 |
| abstract_inverted_index.based | 3 |
| abstract_inverted_index.bones | 45 |
| abstract_inverted_index.first | 74 |
| abstract_inverted_index.great | 12, 139 |
| abstract_inverted_index.image | 135 |
| abstract_inverted_index.novel | 28 |
| abstract_inverted_index.prior | 48 |
| abstract_inverted_index.shows | 138 |
| abstract_inverted_index.spine | 1, 36, 44, 134 |
| abstract_inverted_index.their | 51 |
| abstract_inverted_index.value | 13 |
| abstract_inverted_index.which | 137 |
| abstract_inverted_index.(VPI), | 9 |
| abstract_inverted_index.encode | 62 |
| abstract_inverted_index.images | 37 |
| abstract_inverted_index.means, | 100 |
| abstract_inverted_index.method | 129 |
| abstract_inverted_index.paper, | 24 |
| abstract_inverted_index.shapes | 52 |
| abstract_inverted_index.strong | 47 |
| abstract_inverted_index.volume | 6 |
| abstract_inverted_index.conduct | 121 |
| abstract_inverted_index.contain | 46 |
| abstract_inverted_index.images, | 58 |
| abstract_inverted_index.imaging | 8 |
| abstract_inverted_index.improve | 31 |
| abstract_inverted_index.learned | 112 |
| abstract_inverted_index.manner. | 72 |
| abstract_inverted_index.network | 102 |
| abstract_inverted_index.present | 84 |
| abstract_inverted_index.propose | 26, 60 |
| abstract_inverted_index.revisit | 75 |
| abstract_inverted_index.various | 122 |
| abstract_inverted_index.accuracy | 34 |
| abstract_inverted_index.achieves | 130 |
| abstract_inverted_index.clinical | 15, 142 |
| abstract_inverted_index.diagnose | 18 |
| abstract_inverted_index.explores | 103 |
| abstract_inverted_index.improves | 116 |
| abstract_inverted_index.proposed | 128 |
| abstract_inverted_index.semantic | 67 |
| abstract_inverted_index.strategy | 86 |
| abstract_inverted_index.Automatic | 0 |
| abstract_inverted_index.accuracy. | 119 |
| abstract_inverted_index.attentive | 40, 71 |
| abstract_inverted_index.features, | 113 |
| abstract_inverted_index.framework | 29 |
| abstract_inverted_index.introduce | 88 |
| abstract_inverted_index.knowledge | 49, 91 |
| abstract_inverted_index.learning, | 81 |
| abstract_inverted_index.learning. | 41 |
| abstract_inverted_index.mechanism | 78 |
| abstract_inverted_index.positions | 54 |
| abstract_inverted_index.potential | 140 |
| abstract_inverted_index.promising | 131 |
| abstract_inverted_index.scoliosis | 19 |
| abstract_inverted_index.contextual | 106 |
| abstract_inverted_index.diagnosis. | 143 |
| abstract_inverted_index.projection | 7 |
| abstract_inverted_index.structural | 90, 108 |
| abstract_inverted_index.teenagers. | 21 |
| abstract_inverted_index.ultrasound | 5, 56 |
| abstract_inverted_index.demonstrate | 125 |
| abstract_inverted_index.experiments | 123 |
| abstract_inverted_index.information | 64, 109 |
| abstract_inverted_index.performance | 132 |
| abstract_inverted_index.applications | 16 |
| abstract_inverted_index.consequently | 115 |
| abstract_inverted_index.segmentation | 33, 118 |
| abstract_inverted_index.segmentation, | 2, 136 |
| abstract_inverted_index.representation | 80, 95 |
| abstract_inverted_index.self-attention | 77 |
| abstract_inverted_index.representations | 68 |
| abstract_inverted_index.self-attention. | 97 |
| abstract_inverted_index.structure-enhanced | 39 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 10 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.57096618 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |