Matches in SemOpenAlex for { <https://semopenalex.org/work/W3115187587> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W3115187587 endingPage "432" @default.
- W3115187587 startingPage "420" @default.
- W3115187587 abstract "This study analyses the use of a pixel classification model to segment amniotic fluid areas on ultrasound (US) images characterized by noise, blurry edge, artifacts, and low contrast. In contrast with the previous methods, this study constrains a training set of pixels based on neighbourhood information with the rectangle window sampling method used to determine the characteristics of each pixel in its environment specifically. The feature extraction is no longer based on the global characteristics of the object rather by taking the value of each pixel in the object area using the sampling window. This research also combines the local first-order statistical methods and gray level information in the window to obtain the characteristics of each pixel. Furthermore, Random Forest and Decision Tree (C.45) were used to classify each pixel into four classes, namely amniotic fluid, placenta, uterus, and fetal body. The classification performance testing of pixel sampling data showed that the Random forest with 5 × 7 window sizes achieved the highest performance at 99.5% accuracy, precision, and recall, respectively. Furthermore, the proposed model was evaluated using 50 new test US images to segment the amniotic fluid area. According to experimental result, proposed models can produce better segmentation area with an increase in the IoU value by 18.3% or a Jaccard coefficient value rate of 0.183 in the range of 0-1 with the previous state of the art method. Furthermore, the proposed model reduces the error rate and improves accuracy by 6.61% and 84.77%, respectively." @default.
- W3115187587 created "2021-01-05" @default.
- W3115187587 creator A5021646844 @default.
- W3115187587 creator A5068789143 @default.
- W3115187587 date "2021-02-28" @default.
- W3115187587 modified "2023-09-24" @default.
- W3115187587 title "Pixel Classification Based on Local Gray Level Rectangle Window Sampling for Amniotic Fluid Segmentation" @default.
- W3115187587 cites W2004436528 @default.
- W3115187587 cites W2014418634 @default.
- W3115187587 cites W2018893586 @default.
- W3115187587 cites W2067843516 @default.
- W3115187587 cites W2091967951 @default.
- W3115187587 cites W2152605768 @default.
- W3115187587 cites W2175650166 @default.
- W3115187587 cites W2255915677 @default.
- W3115187587 cites W2754228587 @default.
- W3115187587 cites W2761877971 @default.
- W3115187587 cites W2773747586 @default.
- W3115187587 cites W2791787650 @default.
- W3115187587 cites W2976548293 @default.
- W3115187587 cites W2985868371 @default.
- W3115187587 cites W3013930300 @default.
- W3115187587 doi "https://doi.org/10.22266/ijies2021.0228.39" @default.
- W3115187587 hasPublicationYear "2021" @default.
- W3115187587 type Work @default.
- W3115187587 sameAs 3115187587 @default.
- W3115187587 citedByCount "3" @default.
- W3115187587 countsByYear W31151875872022 @default.
- W3115187587 crossrefType "journal-article" @default.
- W3115187587 hasAuthorship W3115187587A5021646844 @default.
- W3115187587 hasAuthorship W3115187587A5068789143 @default.
- W3115187587 hasBestOaLocation W31151875871 @default.
- W3115187587 hasConcept C153180895 @default.
- W3115187587 hasConcept C154945302 @default.
- W3115187587 hasConcept C160633673 @default.
- W3115187587 hasConcept C169258074 @default.
- W3115187587 hasConcept C203519979 @default.
- W3115187587 hasConcept C2524010 @default.
- W3115187587 hasConcept C2781302577 @default.
- W3115187587 hasConcept C31972630 @default.
- W3115187587 hasConcept C33923547 @default.
- W3115187587 hasConcept C41008148 @default.
- W3115187587 hasConcept C89600930 @default.
- W3115187587 hasConceptScore W3115187587C153180895 @default.
- W3115187587 hasConceptScore W3115187587C154945302 @default.
- W3115187587 hasConceptScore W3115187587C160633673 @default.
- W3115187587 hasConceptScore W3115187587C169258074 @default.
- W3115187587 hasConceptScore W3115187587C203519979 @default.
- W3115187587 hasConceptScore W3115187587C2524010 @default.
- W3115187587 hasConceptScore W3115187587C2781302577 @default.
- W3115187587 hasConceptScore W3115187587C31972630 @default.
- W3115187587 hasConceptScore W3115187587C33923547 @default.
- W3115187587 hasConceptScore W3115187587C41008148 @default.
- W3115187587 hasConceptScore W3115187587C89600930 @default.
- W3115187587 hasIssue "1" @default.
- W3115187587 hasLocation W31151875871 @default.
- W3115187587 hasOpenAccess W3115187587 @default.
- W3115187587 hasPrimaryLocation W31151875871 @default.
- W3115187587 hasRelatedWork W1669643531 @default.
- W3115187587 hasRelatedWork W2005437358 @default.
- W3115187587 hasRelatedWork W2039154422 @default.
- W3115187587 hasRelatedWork W2090093270 @default.
- W3115187587 hasRelatedWork W2134924024 @default.
- W3115187587 hasRelatedWork W2517104666 @default.
- W3115187587 hasRelatedWork W2739874619 @default.
- W3115187587 hasRelatedWork W2903975345 @default.
- W3115187587 hasRelatedWork W3017840285 @default.
- W3115187587 hasRelatedWork W3039022597 @default.
- W3115187587 hasVolume "14" @default.
- W3115187587 isParatext "false" @default.
- W3115187587 isRetracted "false" @default.
- W3115187587 magId "3115187587" @default.
- W3115187587 workType "article" @default.