176 related articles for article (PubMed ID: 35684680)
1. Nuclei-Guided Network for Breast Cancer Grading in HE-Stained Pathological Images.
Yan R; Ren F; Li J; Rao X; Lv Z; Zheng C; Zhang F
Sensors (Basel); 2022 May; 22(11):. PubMed ID: 35684680
[TBL] [Abstract][Full Text] [Related]
2. Divide-and-Attention Network for HE-Stained Pathological Image Classification.
Yan R; Yang Z; Li J; Zheng C; Zhang F
Biology (Basel); 2022 Jun; 11(7):. PubMed ID: 36101363
[TBL] [Abstract][Full Text] [Related]
3. Tumor grading model employing geometric analysis of histopathological images with characteristic nuclei dictionary.
Brindha V; Jayashree P; Karthik P; Manikandan P
Comput Biol Med; 2022 Oct; 149():106008. PubMed ID: 36030720
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Nuclei segmentation of HE stained histopathological images based on feature global delivery connection network.
Shi P; Zhong J; Lin L; Lin L; Li H; Wu C
PLoS One; 2022; 17(9):e0273682. PubMed ID: 36107930
[TBL] [Abstract][Full Text] [Related]
6. New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images.
Chen JM; Qu AP; Wang LW; Yuan JP; Yang F; Xiang QM; Maskey N; Yang GF; Liu J; Li Y
Sci Rep; 2015 May; 5():10690. PubMed ID: 26022540
[TBL] [Abstract][Full Text] [Related]
7. Segmentation of HE-stained meningioma pathological images based on pseudo-labels.
Wu C; Zhong J; Lin L; Chen Y; Xue Y; Shi P
PLoS One; 2022; 17(2):e0263006. PubMed ID: 35120175
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Triple U-net: Hematoxylin-aware nuclei segmentation with progressive dense feature aggregation.
Zhao B; Chen X; Li Z; Yu Z; Yao S; Yan L; Wang Y; Liu Z; Liang C; Han C
Med Image Anal; 2020 Oct; 65():101786. PubMed ID: 32712523
[TBL] [Abstract][Full Text] [Related]
10. FEEDNet: a feature enhanced encoder-decoder LSTM network for nuclei instance segmentation for histopathological diagnosis.
Deshmukh G; Susladkar O; Makwana D; Chandra Teja R S; Kumar S N; Mittal S
Phys Med Biol; 2022 Sep; 67(19):. PubMed ID: 35905732
[No Abstract] [Full Text] [Related]
11. Segmentation of Breast Tubules in H&E Images Based on a DKS-DoubleU-Net Model.
Chen Y; Zhou Y; Chen G; Guo Y; Lv Y; Ma M; Pei Z; Sun Z
Biomed Res Int; 2022; 2022():2961610. PubMed ID: 36246965
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Dual Encoder Attention U-net for Nuclei Segmentation.
Vahadane A; B A; Majumdar S
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3205-3208. PubMed ID: 34891923
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Nuclei detection in breast histopathology images with iterative correction.
Liu Z; Cai Y; Tang Q
Med Biol Eng Comput; 2024 Feb; 62(2):465-478. PubMed ID: 37914958
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Nuclei Segmentation on Histopathology Images of Breast Carcinoma.
Ramirez Guatemala-Sanchez VY; Peregrina-Barreto H; Lopez-Armas G
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():2622-2628. PubMed ID: 34891791
[TBL] [Abstract][Full Text] [Related]
18. Detection of malignant melanoma in H&E-stained images using deep learning techniques.
Alheejawi S; Berendt R; Jha N; Maity SP; Mandal M
Tissue Cell; 2021 Dec; 73():101659. PubMed ID: 34634635
[TBL] [Abstract][Full Text] [Related]
19. Computer-aided classification of breast cancer nuclei.
Schnorrenberg F; Pattichis CS; Schizas CN; Kyriacou K; Vassiliou M
Technol Health Care; 1996 Aug; 4(2):147-61. PubMed ID: 8885093
[TBL] [Abstract][Full Text] [Related]
20. Detection of Breast Cancer with Lightweight Deep Neural Networks for Histology Image Classification.
Laxmisagar HS; Hanumantharaju MC
Crit Rev Biomed Eng; 2022; 50(2):1-19. PubMed ID: 36374820
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]