Matches in SemOpenAlex for { <https://semopenalex.org/work/W2999611744> ?p ?o ?g. }
- W2999611744 endingPage "107200" @default.
- W2999611744 startingPage "107200" @default.
- W2999611744 abstract "Estrogen and progesterone receptors serve as an important predictive and prognostic biomarkers for breast cancer immunohistological analysis. For breast cancer prognosis, pathologists manually compute the score based on the visual expression and the number of immunopositive and immunonegative nuclei. This manual scoring technique is time-consuming, cumbersome, expensive, error-prone, and susceptible to intra- and interobserver ambiguities. To solve these issues, we proposed a deep neural network (i.e., HscoreNet), which consists of three parts, i.e., encoder, decoder, and scoring layer. A total of 600 (300 ER and 300 PR) regions of interest at 40 × magnification from 100 histologically confirmed slides were used in this study. The size of each region of interest was 2048 × 1536 pixels (width × height). The encoder layer has been used to transform input pixels into a lower-dimensional representation, whereas the decoder reconstructs the output of the encoder through minimization of a cost function. The decoder generates an image that only contains immunopositive and immunonegative nuclei. The output of the decoder is fed to the input of the scoring layer. This layer computes the Histo-score or H-score based on the staining intensity, the color expression, and the number of immunopositive and immunonegative nuclei. Pathologists compute this score to subcategorize the cancer grades and to decide proper treatment procedures. Our proposed approach is affordable, accurate, and fast. We achieved excellent performance, with 95.87% precision and 94.53% classification accuracy. Our proposed approach streamlines the human error-prone and time-consuming process. This methodology can also be used for other types of histology and immunohistology image segmentation and scoring." @default.
- W2999611744 created "2020-01-23" @default.
- W2999611744 creator A5008847838 @default.
- W2999611744 creator A5009776620 @default.
- W2999611744 creator A5017647198 @default.
- W2999611744 creator A5022432777 @default.
- W2999611744 creator A5085420736 @default.
- W2999611744 date "2020-06-01" @default.
- W2999611744 modified "2023-09-29" @default.
- W2999611744 title "HscoreNet: A Deep network for estrogen and progesterone scoring using breast IHC images" @default.
- W2999611744 cites W1757407923 @default.
- W2999611744 cites W1965120554 @default.
- W2999611744 cites W1970120446 @default.
- W2999611744 cites W1979426842 @default.
- W2999611744 cites W2017257315 @default.
- W2999611744 cites W2036304194 @default.
- W2999611744 cites W2049114438 @default.
- W2999611744 cites W2051765910 @default.
- W2999611744 cites W2067199269 @default.
- W2999611744 cites W2082165791 @default.
- W2999611744 cites W2082724230 @default.
- W2999611744 cites W2083647740 @default.
- W2999611744 cites W2110141736 @default.
- W2999611744 cites W2128480523 @default.
- W2999611744 cites W2133554539 @default.
- W2999611744 cites W2137773299 @default.
- W2999611744 cites W2143251344 @default.
- W2999611744 cites W2144705783 @default.
- W2999611744 cites W2149544548 @default.
- W2999611744 cites W2158805232 @default.
- W2999611744 cites W2248620004 @default.
- W2999611744 cites W2280351290 @default.
- W2999611744 cites W2292929912 @default.
- W2999611744 cites W2295468633 @default.
- W2999611744 cites W2312404985 @default.
- W2999611744 cites W2344147939 @default.
- W2999611744 cites W2550409828 @default.
- W2999611744 cites W2603986758 @default.
- W2999611744 cites W2604440528 @default.
- W2999611744 cites W2615195201 @default.
- W2999611744 cites W2622279389 @default.
- W2999611744 cites W2731900166 @default.
- W2999611744 cites W2733771079 @default.
- W2999611744 cites W2790813572 @default.
- W2999611744 cites W2883567318 @default.
- W2999611744 cites W2901364394 @default.
- W2999611744 cites W2913943056 @default.
- W2999611744 cites W2918930673 @default.
- W2999611744 cites W2944539652 @default.
- W2999611744 cites W2946039882 @default.
- W2999611744 cites W2954203073 @default.
- W2999611744 cites W2963392702 @default.
- W2999611744 cites W3104390926 @default.
- W2999611744 doi "https://doi.org/10.1016/j.patcog.2020.107200" @default.
- W2999611744 hasPublicationYear "2020" @default.
- W2999611744 type Work @default.
- W2999611744 sameAs 2999611744 @default.
- W2999611744 citedByCount "14" @default.
- W2999611744 countsByYear W29996117442021 @default.
- W2999611744 countsByYear W29996117442022 @default.
- W2999611744 countsByYear W29996117442023 @default.
- W2999611744 crossrefType "journal-article" @default.
- W2999611744 hasAuthorship W2999611744A5008847838 @default.
- W2999611744 hasAuthorship W2999611744A5009776620 @default.
- W2999611744 hasAuthorship W2999611744A5017647198 @default.
- W2999611744 hasAuthorship W2999611744A5022432777 @default.
- W2999611744 hasAuthorship W2999611744A5085420736 @default.
- W2999611744 hasConcept C111919701 @default.
- W2999611744 hasConcept C11413529 @default.
- W2999611744 hasConcept C118505674 @default.
- W2999611744 hasConcept C121608353 @default.
- W2999611744 hasConcept C126322002 @default.
- W2999611744 hasConcept C153180895 @default.
- W2999611744 hasConcept C154945302 @default.
- W2999611744 hasConcept C160633673 @default.
- W2999611744 hasConcept C41008148 @default.
- W2999611744 hasConcept C4144372 @default.
- W2999611744 hasConcept C50644808 @default.
- W2999611744 hasConcept C530470458 @default.
- W2999611744 hasConcept C71924100 @default.
- W2999611744 hasConcept C84606932 @default.
- W2999611744 hasConcept C98717036 @default.
- W2999611744 hasConceptScore W2999611744C111919701 @default.
- W2999611744 hasConceptScore W2999611744C11413529 @default.
- W2999611744 hasConceptScore W2999611744C118505674 @default.
- W2999611744 hasConceptScore W2999611744C121608353 @default.
- W2999611744 hasConceptScore W2999611744C126322002 @default.
- W2999611744 hasConceptScore W2999611744C153180895 @default.
- W2999611744 hasConceptScore W2999611744C154945302 @default.
- W2999611744 hasConceptScore W2999611744C160633673 @default.
- W2999611744 hasConceptScore W2999611744C41008148 @default.
- W2999611744 hasConceptScore W2999611744C4144372 @default.
- W2999611744 hasConceptScore W2999611744C50644808 @default.
- W2999611744 hasConceptScore W2999611744C530470458 @default.
- W2999611744 hasConceptScore W2999611744C71924100 @default.
- W2999611744 hasConceptScore W2999611744C84606932 @default.
- W2999611744 hasConceptScore W2999611744C98717036 @default.
- W2999611744 hasFunder F4320320719 @default.