Show simple item record

dc.contributor.authorCHEN Sishuo, WANG Xiaodong, LIU Xiyang
dc.contributor.otherSchool of Computer Science and Technology,Xidian University,Xi’an 710126,China
dc.date.accessioned2025-08-27T02:40:24Z
dc.date.accessioned2025-10-08T09:26:53Z
dc.date.available2025-10-08T09:26:53Z
dc.date.issued01-06-2024
dc.identifier.urihttp://digilib.fisipol.ugm.ac.id/repo/handle/15717717/40415
dc.description.abstractPathological diagnosis is the gold standard for cancer diagnosis and treatment,the use of artificial intelligence(AI) models for analyzing pathological images has the potential to not only reduce the workload of pathologists but also improve the accuracy of cancer diagnosis and treatment.However,these methods face challenges due to the large scale of pathological images and the difficulty in interpreting the predicted results.In recent studies,graph neural networks have shown their strong abilities in modeling spatial context and interpretability of entities in images,which provides a new idea for the study of digital pathology.In this survey,we review recent related works in computer vision,analyze the advantages of graph neural networks for breast cancer pathology,classify and compare existing graph construction methods,and analyze and compare graph neural network models proposed in recent years.We also summarize the challenges that exist in using graph neural networks for analyzing pathological images of breast cancer and prospect the future research directions.
dc.language.isoZH
dc.publisherEditorial office of Computer Science
dc.subject.lccComputer software
dc.titleSurvey of Breast Cancer Pathological Image Analysis Methods Based on Graph Neural Networks
dc.typeArticle
dc.description.keywordsbreast cancer pathological image|graph neural network|graph classification|digital pathology
dc.description.pages172-185
dc.description.doi10.11896/jsjkx.230400106
dc.title.journalJisuanji kexue
dc.identifier.oaioai:doaj.org/journal:410eee8751ec40dc94b94fbe54586656
dc.journal.infoVolume 51, Issue 6


This item appears in the following Collection(s)

Show simple item record