These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
870 related articles for article (PubMed ID: 30337080)
1. Fast unsupervised nuclear segmentation and classification scheme for automatic allred cancer scoring in immunohistochemical breast tissue images. Mouelhi A; Rmili H; Ali JB; Sayadi M; Doghri R; Mrad K Comput Methods Programs Biomed; 2018 Oct; 165():37-51. PubMed ID: 30337080 [TBL] [Abstract][Full Text] [Related]
2. A new automatic image analysis method for assessing estrogen receptors' status in breast tissue specimens. Mouelhi A; Sayadi M; Fnaiech F; Mrad K; Ben Romdhane K Comput Biol Med; 2013 Dec; 43(12):2263-77. PubMed ID: 24290943 [TBL] [Abstract][Full Text] [Related]
3. Performance evaluation of maximal separation techniques in immunohistochemical scoring of tissue images. Hameed KA; Banumathi A; Ulaganathan G Micron; 2015 Dec; 79():29-35. PubMed ID: 26313715 [TBL] [Abstract][Full Text] [Related]
4. AutoIHC-scoring: a machine learning framework for automated Allred scoring of molecular expression in ER- and PR-stained breast cancer tissue. Tewary S; Arun I; Ahmed R; Chatterjee S; Chakraborty C J Microsc; 2017 Nov; 268(2):172-185. PubMed ID: 28613390 [TBL] [Abstract][Full Text] [Related]
5. Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer. Krecsák L; Micsik T; Kiszler G; Krenács T; Szabó D; Jónás V; Császár G; Czuni L; Gurzó P; Ficsor L; Molnár B Diagn Pathol; 2011 Jan; 6():6. PubMed ID: 21244664 [TBL] [Abstract][Full Text] [Related]
6. AutoIHC-Analyzer: computer-assisted microscopy for automated membrane extraction/scoring in HER2 molecular markers. Tewary S; Arun I; Ahmed R; Chatterjee S; Mukhopadhyay S J Microsc; 2021 Jan; 281(1):87-96. PubMed ID: 32803890 [TBL] [Abstract][Full Text] [Related]
7. Automated cell nuclear segmentation in color images of hematoxylin and eosin-stained breast biopsy. Latson L; Sebek B; Powell KA Anal Quant Cytol Histol; 2003 Dec; 25(6):321-31. PubMed ID: 14714298 [TBL] [Abstract][Full Text] [Related]
8. Breast cancer subtype discrimination using standardized 4-IHC and digital image analysis. Gándara-Cortes M; Vázquez-Boquete Á; Fernández-Rodríguez B; Viaño P; Ínsua D; Seoane-Seoane A; Gude F; Gallego R; Fraga M; Antúnez JR; Curiel T; Pérez-López E; García-Caballero T Virchows Arch; 2018 Feb; 472(2):195-203. PubMed ID: 28825136 [TBL] [Abstract][Full Text] [Related]
9. Comparison of immunohistochemistry with PCR for assessment of ER, PR, and Ki-67 and prediction of pathological complete response in breast cancer. Sinn HP; Schneeweiss A; Keller M; Schlombs K; Laible M; Seitz J; Lakis S; Veltrup E; Altevogt P; Eidt S; Wirtz RM; Marmé F BMC Cancer; 2017 Feb; 17(1):124. PubMed ID: 28193205 [TBL] [Abstract][Full Text] [Related]
10. An optimized image analysis algorithm for detecting nuclear signals in digital whole slides for histopathology. Paulik R; Micsik T; Kiszler G; Kaszál P; Székely J; Paulik N; Várhalmi E; Prémusz V; Krenács T; Molnár B Cytometry A; 2017 Jun; 91(6):595-608. PubMed ID: 28472544 [TBL] [Abstract][Full Text] [Related]
11. Performance comparison of machine learning methods for prognosis of hormone receptor status in breast cancer tissue samples. Kalinli A; Sarikoc F; Akgun H; Ozturk F Comput Methods Programs Biomed; 2013 Jun; 110(3):298-307. PubMed ID: 23339901 [TBL] [Abstract][Full Text] [Related]
12. Study on breast carcinoma Her2/neu and hormonal receptors status assessed by automated images analysis systems: ACIS III (Dako) and ScanScope (Aperio). Słodkowska J; Filas V; Buszkiewicz E; Trzeciak P; Wojciechowski M; Koktysz R; Staniszewski W; Breborowicz J; Rojo MG Folia Histochem Cytobiol; 2010 Jan; 48(1):19-25. PubMed ID: 20529811 [TBL] [Abstract][Full Text] [Related]
13. Computer-based association of the texture of expressed estrogen receptor nuclei with histologic grade using immunohistochemically-stained breast carcinomas. Kostopoulos S; Glotsos D; Cavouras D; Daskalakis A; Kalatzis I; Georgiadis P; Bougioukos P; Ravazoula P; Nikiforidis G Anal Quant Cytol Histol; 2009 Aug; 31(4):187-96. PubMed ID: 19736866 [TBL] [Abstract][Full Text] [Related]
14. Using cell nuclei features to detect colon cancer tissue in hematoxylin and eosin stained slides. Jørgensen AS; Rasmussen AM; Andersen NKM; Andersen SK; Emborg J; Røge R; Østergaard LR Cytometry A; 2017 Aug; 91(8):785-793. PubMed ID: 28727286 [TBL] [Abstract][Full Text] [Related]
15. Automatic segmentation of cell nuclei in Feulgen-stained histological sections of prostate cancer and quantitative evaluation of segmentation results. Nielsen B; Albregtsen F; Danielsen HE Cytometry A; 2012 Jul; 81(7):588-601. PubMed ID: 22605528 [TBL] [Abstract][Full Text] [Related]
16. Comparative analysis of methods for accurate recognition of cells through nuclei staining of Ki-67 in neuroblastoma and estrogen/progesterone status staining in breast cancer. Markiewicz T; Wisniewski P; Osowski S; Patera J; Kozlowski W; Koktysz R Anal Quant Cytol Histol; 2009 Feb; 31(1):49-62. PubMed ID: 19320193 [TBL] [Abstract][Full Text] [Related]
17. Automated segmentation and classification of cell nuclei in immunohistochemical breast cancer images with estrogen receptor marker. Oscanoa J; Doimi F; Dyer R; Araujo J; Pinto J; Castaneda B Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():2399-2402. PubMed ID: 28268808 [TBL] [Abstract][Full Text] [Related]
18. Automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on whole tissue sections in breast carcinoma. Feng M; Deng Y; Yang L; Jing Q; Zhang Z; Xu L; Wei X; Zhou Y; Wu D; Xiang F; Wang Y; Bao J; Bu H Diagn Pathol; 2020 May; 15(1):65. PubMed ID: 32471471 [TBL] [Abstract][Full Text] [Related]
19. Breast cancer histopathological images recognition based on two-stage nuclei segmentation strategy. Hu H; Qiao S; Hao Y; Bai Y; Cheng R; Zhang W; Zhang G PLoS One; 2022; 17(4):e0266973. PubMed ID: 35482728 [TBL] [Abstract][Full Text] [Related]
20. Exploring the spatial dimension of estrogen and progesterone signaling: detection of nuclear labeling in lobular epithelial cells in normal mammary glands adjacent to breast cancer. Grote A; Abbas M; Linder N; Kreipe HH; Lundin J; Feuerhake F Diagn Pathol; 2014; 9 Suppl 1(Suppl 1):S11. PubMed ID: 25565114 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]