Journal article 13 views
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations
IET Systems Biology
Swansea University Author:
Cheng Cheng
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1049/syb2.70055
Abstract
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations
| Published in: | IET Systems Biology |
|---|---|
| ISSN: | 1751-8849 1751-8857 |
| Published: |
Wiley
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71290 |
| first_indexed |
2026-01-21T14:58:44Z |
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| last_indexed |
2026-02-04T05:33:38Z |
| id |
cronfa71290 |
| recordtype |
SURis |
| fullrecord |
<?xml version="1.0"?><rfc1807><datestamp>2026-02-03T09:42:46.2326670</datestamp><bib-version>v2</bib-version><id>71290</id><entry>2026-01-21</entry><title>TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations</title><swanseaauthors><author><sid>11ddf61c123b99e59b00fa1479367582</sid><ORCID>0000-0003-0371-9646</ORCID><firstname>Cheng</firstname><surname>Cheng</surname><name>Cheng Cheng</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2026-01-21</date><deptcode>MACS</deptcode><abstract/><type>Journal Article</type><journal>IET Systems Biology</journal><volume/><journalNumber/><paginationStart/><paginationEnd/><publisher>Wiley</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1751-8849</issnPrint><issnElectronic>1751-8857</issnElectronic><keywords>Nucleus segmentation; Constraint networks; Segmentation networks; Attention networks; Confident learning</keywords><publishedDay>0</publishedDay><publishedMonth>0</publishedMonth><publishedYear>0</publishedYear><publishedDate>0001-01-01</publishedDate><doi>10.1049/syb2.70055</doi><url/><notes/><college>COLLEGE NANME</college><department>Mathematics and Computer Science School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MACS</DepartmentCode><institution>Swansea University</institution><apcterm>SU Library paid the OA fee (TA Institutional Deal)</apcterm><funders>This work was funded by by UKRI Grant EP/W020408/1 and Grant RS718 through Doctoral Training Centre at Swansea University.</funders><projectreference/><lastEdited>2026-02-03T09:42:46.2326670</lastEdited><Created>2026-01-21T14:50:35.0358193</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>Shaoqiang</firstname><surname>Wang</surname><orcid>0000-0002-7539-5970</orcid><order>1</order></author><author><firstname>Guiling</firstname><surname>Shi</surname><order>2</order></author><author><firstname>Yuchen</firstname><surname>Wang</surname><order>3</order></author><author><firstname>Qiang</firstname><surname>Li</surname><order>4</order></author><author><firstname>Yawu</firstname><surname>Zhao</surname><order>5</order></author><author><firstname>Cheng</firstname><surname>Cheng</surname><orcid>0000-0003-0371-9646</orcid><order>6</order></author></authors><documents/><OutputDurs/></rfc1807> |
| spelling |
2026-02-03T09:42:46.2326670 v2 71290 2026-01-21 TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations 11ddf61c123b99e59b00fa1479367582 0000-0003-0371-9646 Cheng Cheng Cheng Cheng true false 2026-01-21 MACS Journal Article IET Systems Biology Wiley 1751-8849 1751-8857 Nucleus segmentation; Constraint networks; Segmentation networks; Attention networks; Confident learning 0 0 0 0001-01-01 10.1049/syb2.70055 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University SU Library paid the OA fee (TA Institutional Deal) This work was funded by by UKRI Grant EP/W020408/1 and Grant RS718 through Doctoral Training Centre at Swansea University. 2026-02-03T09:42:46.2326670 2026-01-21T14:50:35.0358193 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Shaoqiang Wang 0000-0002-7539-5970 1 Guiling Shi 2 Yuchen Wang 3 Qiang Li 4 Yawu Zhao 5 Cheng Cheng 0000-0003-0371-9646 6 |
| title |
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations |
| spellingShingle |
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations Cheng Cheng |
| title_short |
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations |
| title_full |
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations |
| title_fullStr |
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations |
| title_full_unstemmed |
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations |
| title_sort |
TSSP-UNet: A Two-stage Weakly Supervised Pathological Image Segmentation with Point Annotations |
| author_id_str_mv |
11ddf61c123b99e59b00fa1479367582 |
| author_id_fullname_str_mv |
11ddf61c123b99e59b00fa1479367582_***_Cheng Cheng |
| author |
Cheng Cheng |
| author2 |
Shaoqiang Wang Guiling Shi Yuchen Wang Qiang Li Yawu Zhao Cheng Cheng |
| format |
Journal article |
| container_title |
IET Systems Biology |
| institution |
Swansea University |
| issn |
1751-8849 1751-8857 |
| doi_str_mv |
10.1049/syb2.70055 |
| publisher |
Wiley |
| college_str |
Faculty of Science and Engineering |
| hierarchytype |
|
| hierarchy_top_id |
facultyofscienceandengineering |
| hierarchy_top_title |
Faculty of Science and Engineering |
| hierarchy_parent_id |
facultyofscienceandengineering |
| hierarchy_parent_title |
Faculty of Science and Engineering |
| department_str |
School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science |
| document_store_str |
0 |
| active_str |
0 |
| published_date |
0001-01-01T05:33:44Z |
| _version_ |
1856805823873810432 |
| score |
11.09611 |

