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Unsupervised domain adaptation for nuclei segmentation: Adapting from hematoxylin & eosin stained slides to immunohistochemistry stained slides using a curriculum approach

Computer Methods and Programs in Biomedicine(2023)10.1016/j.cmpb.2023.107768Source: DataRank Database

Unsupervised domain adaptation for nuclei segmentation: Adapting from hematoxylin & eosin stained slides to immunohistochemistry stained slides using a curriculum approach is a research paper published in Computer Methods and Programs in Biomedicine (2023). On theSindex it has a DataRank of 0. It has been cited 12 times.

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12 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (9 grants)Impact (FWCI 1.57)OA: closedTopics (22)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (0/2)

Interoperable (0/2)

Reusable (0/3)

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Authors (7)

Ruichen Rong ORCID,Zifan Gu ORCID,Junya Fujimoto ORCID,Xiaowei Zhan ORCID,Yang Xie ORCID

Live enrichment

PubMed:37619429 OpenAlex:https://openalex.org/W4386002401

National Institutes of Health

Grant: P50CA70907

National Institutes of Health

Grant: R01DE030656

National Institutes of Health

Grant: R01GM115473

National Institutes of Health

Grant: R01GM140012

National Institutes of Health

Grant: R35GM136375

National Institutes of Health

Grant: U01CA249245

Cancer Prevention and Research Institute of Texas

Grant: RP180805

Cancer Prevention and Research Institute of Texas

Grant: RP190107

Cancer Prevention and Research Institute of Texas

Grant: RP230330

FWCI

1.57

Citation Percentile

0.9%

Citation Trend

2023

2024

2025

2026

closedLicense: https://doi.org/10.15223/policy-004

publisherhttps://api.elsevier.com/content/article/PII:S0169260723004340?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S0169260723004340?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.cmpb.2023.107768

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37619429

Fields of Study

AI in cancer detectionDomain Adaptation and Few-Shot LearningMedical Image Segmentation TechniquesEosine Yellowish-(YS)HematoxylinImmunohistochemistryCurriculumAlgorithms

MeSH Terms

AlgorithmsCurriculumEosine Yellowish-(YS)HematoxylinImmunohistochemistry

Keywords

Computer scienceSegmentationArtificial intelligencePattern recognition (psychology)Nuclear SegmentationInstance SegmentationPathology ImageUnsupervised Domain AdaptationCurriculum Learning

Sustainable Development Goals

SDG 0: Reduced inequalities

Unsupervised domain adaptation for nuclei segmentation: Adapting from hematoxylin & eosin stained slides to immunohistochemistry stained slides using a curriculum approach

FAIR Checklist

Authors (7)

Funding (9 grants)

Impact

Open Access

Topics