168 related articles for article (PubMed ID: 37620357)
1. A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics.
Weitz P; Valkonen M; Solorzano L; Carr C; Kartasalo K; Boissin C; Koivukoski S; Kuusela A; Rasic D; Feng Y; Sinius Pouplier S; Sharma A; Ledesma Eriksson K; Latonen L; Laenkholm AV; Hartman J; Ruusuvuori P; Rantalainen M
Sci Data; 2023 Aug; 10(1):562. PubMed ID: 37620357
[TBL] [Abstract][Full Text] [Related]
2. Fast cross-staining alignment of gigapixel whole slide images with application to prostate cancer and breast cancer analysis.
Wang CW; Lee YC; Khalil MA; Lin KY; Yu CP; Lien HC
Sci Rep; 2022 Jul; 12(1):11623. PubMed ID: 35803996
[TBL] [Abstract][Full Text] [Related]
3. Multi-institutional comparison of whole slide digital imaging and optical microscopy for interpretation of hematoxylin-eosin-stained breast tissue sections.
Krishnamurthy S; Mathews K; McClure S; Murray M; Gilcrease M; Albarracin C; Spinosa J; Chang B; Ho J; Holt J; Cohen A; Giri D; Garg K; Bassett RL; Liang K
Arch Pathol Lab Med; 2013 Dec; 137(12):1733-9. PubMed ID: 23947655
[TBL] [Abstract][Full Text] [Related]
4. Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.
Yamashita R; Long J; Longacre T; Peng L; Berry G; Martin B; Higgins J; Rubin DL; Shen J
Lancet Oncol; 2021 Jan; 22(1):132-141. PubMed ID: 33387492
[TBL] [Abstract][Full Text] [Related]
5. Normalization of HE-stained histological images using cycle consistent generative adversarial networks.
Runz M; Rusche D; Schmidt S; Weihrauch MR; Hesser J; Weis CA
Diagn Pathol; 2021 Aug; 16(1):71. PubMed ID: 34362386
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. A U-Net based framework to quantify glomerulosclerosis in digitized PAS and H&E stained human tissues.
Gallego J; Swiderska-Chadaj Z; Markiewicz T; Yamashita M; Gabaldon MA; Gertych A
Comput Med Imaging Graph; 2021 Apr; 89():101865. PubMed ID: 33548823
[TBL] [Abstract][Full Text] [Related]
8. Use of Deep Learning to Develop and Analyze Computational Hematoxylin and Eosin Staining of Prostate Core Biopsy Images for Tumor Diagnosis.
Rana A; Lowe A; Lithgow M; Horback K; Janovitz T; Da Silva A; Tsai H; Shanmugam V; Bayat A; Shah P
JAMA Netw Open; 2020 May; 3(5):e205111. PubMed ID: 32432709
[TBL] [Abstract][Full Text] [Related]
9. Automatic Multi-Stain Registration of Whole Slide Images in Histopathology.
Shafique A; Babaie M; Sajadi M; Batten A; Skdar S; Tizhoosh HR
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3622-3625. PubMed ID: 34892022
[TBL] [Abstract][Full Text] [Related]
10. Deep learning based registration of serial whole-slide histopathology images in different stains.
Roy M; Wang F; Teodoro G; Bhattarai S; Bhargava M; Rekha TS; Aneja R; Kong J
J Pathol Inform; 2023; 14():100311. PubMed ID: 37214150
[TBL] [Abstract][Full Text] [Related]
11. Generative adversarial network based digital stain conversion for generating RGB EVG stained image from hyperspectral H&E stained image.
Biswas T; Suzuki H; Ishikawa M; Kobayashi N; Obi T
J Biomed Opt; 2023 May; 28(5):056501. PubMed ID: 37265876
[TBL] [Abstract][Full Text] [Related]
12. Conventional histological and cytological staining with simultaneous immunohistochemistry enabled by invisible chromogens.
Morrison LE; Lefever MR; Lewis HN; Kapadia MJ; Bauer DR
Lab Invest; 2022 May; 102(5):545-553. PubMed ID: 34963687
[TBL] [Abstract][Full Text] [Related]
13. BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images.
Brancati N; Anniciello AM; Pati P; Riccio D; Scognamiglio G; Jaume G; De Pietro G; Di Bonito M; Foncubierta A; Botti G; Gabrani M; Feroce F; Frucci M
Database (Oxford); 2022 Oct; 2022():. PubMed ID: 36251776
[TBL] [Abstract][Full Text] [Related]
14. The prognostic importance of immunohistochemically detected node metastases in resected esophageal adenocarcinoma.
Waterman TA; Hagen JA; Peters JH; DeMeester SR; Taylor CR; Demeester TR
Ann Thorac Surg; 2004 Oct; 78(4):1161-9; discussion 1161-9. PubMed ID: 15464464
[TBL] [Abstract][Full Text] [Related]
15. Dataset of segmented nuclei in hematoxylin and eosin stained histopathology images of ten cancer types.
Hou L; Gupta R; Van Arnam JS; Zhang Y; Sivalenka K; Samaras D; Kurc TM; Saltz JH
Sci Data; 2020 Jun; 7(1):185. PubMed ID: 32561748
[TBL] [Abstract][Full Text] [Related]
16. Comparison of central laboratory assessments of ER, PR, HER2, and Ki67 by IHC/FISH and the corresponding mRNAs (ESR1, PGR, ERBB2, and MKi67) by RT-qPCR on an automated, broadly deployed diagnostic platform.
Wu NC; Wong W; Ho KE; Chu VC; Rizo A; Davenport S; Kelly D; Makar R; Jassem J; Duchnowska R; Biernat W; Radecka B; Fujita T; Klein JL; Stonecypher M; Ohta S; Juhl H; Weidler JM; Bates M; Press MF
Breast Cancer Res Treat; 2018 Nov; 172(2):327-338. PubMed ID: 30120700
[TBL] [Abstract][Full Text] [Related]
17. Improving mitotic cell counting accuracy and efficiency using phosphohistone-H3 (PHH3) antibody counterstained with haematoxylin and eosin as part of breast cancer grading.
Ibrahim A; Toss MS; Makhlouf S; Miligy IM; Minhas F; Rakha EA
Histopathology; 2023 Feb; 82(3):393-406. PubMed ID: 36349500
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Hematoxylin and Eosin Counterstaining Protocol for Immunohistochemistry Interpretation and Diagnosis.
Grosset AA; Loayza-Vega K; Adam-Granger É; Birlea M; Gilks B; Nguyen B; Soucy G; Tran-Thanh D; Albadine R; Trudel D
Appl Immunohistochem Mol Morphol; 2019 Aug; 27(7):558-563. PubMed ID: 29271792
[TBL] [Abstract][Full Text] [Related]
20. Utility of artificial intelligence with deep learning of hematoxylin and eosin-stained whole slide images to predict lymph node metastasis in T1 colorectal cancer using endoscopically resected specimens; prediction of lymph node metastasis in T1 colorectal cancer.
Song JH; Hong Y; Kim ER; Kim SH; Sohn I
J Gastroenterol; 2022 Sep; 57(9):654-666. PubMed ID: 35802259
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
