Matches in SemOpenAlex for { <https://semopenalex.org/work/W4200248908> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W4200248908 abstract "In histopathological analysis of radicular cysts (RCs), lesions in epithelium can provide pathologists with rich information on pathologic degree, which is helpful to determine the type of periapical lesions and make precise treatment planning. Automatic segmentation and localization of epithelium from whole slide images (WSIs) can assist pathologists to complete pathological diagnosis more quickly. However, the class imbalance problem caused by the small proportion of fragmented epithelium in RCs imposes challenge on the typical automatic one-stage segmentation method. In this paper, we proposed a classification-guided segmentation algorithm (CGSA) for accurate segmentation. Our method was a two-stage model, including a classification network for region of interest (ROI) location and a segmentation network guided by classification. The classification stage eliminated most irrelevant areas and alleviated the class imbalance problem faced by the segmentation model. The results of 5-fold cross validation demonstrated that CGSA outperformed the one-stage segmentation method which was lacking in prior epithelium localization information. The epithelium segmentation achieved an overall Dice's coefficient of 0.722, and intersection over union (IoU) of 0.593, which improved by 5.5% and 5.9% respectively compared with the one-stage segmentation method using UNet.Clinical Relevance— This work presents a framework for automatic epithelium segmentation in histopathological images of RCs. It can be applied to make up for the shortcomings of manual annotation which is labor-intensive, time-consuming and objective." @default.
- W4200248908 created "2021-12-31" @default.
- W4200248908 creator A5017699605 @default.
- W4200248908 creator A5027635271 @default.
- W4200248908 creator A5032364522 @default.
- W4200248908 creator A5050108499 @default.
- W4200248908 creator A5055376209 @default.
- W4200248908 creator A5071529609 @default.
- W4200248908 creator A5090196339 @default.
- W4200248908 creator A5090223092 @default.
- W4200248908 date "2021-11-01" @default.
- W4200248908 modified "2023-09-26" @default.
- W4200248908 title "A Classification-Guided Segmentation Algorithm Based on Deep Learning for Epithelium Segmentation in Histopathological Images of Radicular Cysts" @default.
- W4200248908 cites W2133059825 @default.
- W4200248908 cites W2885650974 @default.
- W4200248908 cites W2906328956 @default.
- W4200248908 cites W2921357516 @default.
- W4200248908 cites W2963150697 @default.
- W4200248908 cites W2963351448 @default.
- W4200248908 cites W3004554077 @default.
- W4200248908 cites W3014754116 @default.
- W4200248908 cites W639708223 @default.
- W4200248908 doi "https://doi.org/10.1109/embc46164.2021.9630552" @default.
- W4200248908 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34892058" @default.
- W4200248908 hasPublicationYear "2021" @default.
- W4200248908 type Work @default.
- W4200248908 citedByCount "0" @default.
- W4200248908 crossrefType "proceedings-article" @default.
- W4200248908 hasAuthorship W4200248908A5017699605 @default.
- W4200248908 hasAuthorship W4200248908A5027635271 @default.
- W4200248908 hasAuthorship W4200248908A5032364522 @default.
- W4200248908 hasAuthorship W4200248908A5050108499 @default.
- W4200248908 hasAuthorship W4200248908A5055376209 @default.
- W4200248908 hasAuthorship W4200248908A5071529609 @default.
- W4200248908 hasAuthorship W4200248908A5090196339 @default.
- W4200248908 hasAuthorship W4200248908A5090223092 @default.
- W4200248908 hasConcept C124504099 @default.
- W4200248908 hasConcept C142724271 @default.
- W4200248908 hasConcept C146357865 @default.
- W4200248908 hasConcept C151730666 @default.
- W4200248908 hasConcept C153180895 @default.
- W4200248908 hasConcept C154945302 @default.
- W4200248908 hasConcept C31972630 @default.
- W4200248908 hasConcept C41008148 @default.
- W4200248908 hasConcept C529295009 @default.
- W4200248908 hasConcept C71924100 @default.
- W4200248908 hasConcept C86803240 @default.
- W4200248908 hasConcept C89600930 @default.
- W4200248908 hasConceptScore W4200248908C124504099 @default.
- W4200248908 hasConceptScore W4200248908C142724271 @default.
- W4200248908 hasConceptScore W4200248908C146357865 @default.
- W4200248908 hasConceptScore W4200248908C151730666 @default.
- W4200248908 hasConceptScore W4200248908C153180895 @default.
- W4200248908 hasConceptScore W4200248908C154945302 @default.
- W4200248908 hasConceptScore W4200248908C31972630 @default.
- W4200248908 hasConceptScore W4200248908C41008148 @default.
- W4200248908 hasConceptScore W4200248908C529295009 @default.
- W4200248908 hasConceptScore W4200248908C71924100 @default.
- W4200248908 hasConceptScore W4200248908C86803240 @default.
- W4200248908 hasConceptScore W4200248908C89600930 @default.
- W4200248908 hasFunder F4320321001 @default.
- W4200248908 hasFunder F4320322990 @default.
- W4200248908 hasFunder F4320322999 @default.
- W4200248908 hasLocation W42002489081 @default.
- W4200248908 hasLocation W42002489082 @default.
- W4200248908 hasOpenAccess W4200248908 @default.
- W4200248908 hasPrimaryLocation W42002489081 @default.
- W4200248908 hasRelatedWork W1507266234 @default.
- W4200248908 hasRelatedWork W1631910785 @default.
- W4200248908 hasRelatedWork W1669643531 @default.
- W4200248908 hasRelatedWork W1721780360 @default.
- W4200248908 hasRelatedWork W2110230079 @default.
- W4200248908 hasRelatedWork W2117664411 @default.
- W4200248908 hasRelatedWork W2117933325 @default.
- W4200248908 hasRelatedWork W2122581818 @default.
- W4200248908 hasRelatedWork W2159066190 @default.
- W4200248908 hasRelatedWork W2739874619 @default.
- W4200248908 isParatext "false" @default.
- W4200248908 isRetracted "false" @default.
- W4200248908 workType "article" @default.