Gadermayr M, Gupta L, Appel V, Boor P, Klinkhammer BM, Merhof D (2019) Generative adversarial networks for facilitating stain-independent supervised and unsupervised segmentation: a study on kidney histology. IEEE Trans Med Imaging 38(10):2293–2302

Article  PubMed  Google Scholar 

Zhizhong S, Zhilian L, Wei D, Yuanhan C, Yiming T, Ruizhao L, Xinling L (2019) Evolution of chronic glomerular diseases spectrum and epidemiological characteristics of membranous nephropathy. J Clin Nephrol 19(7):471–476

Google Scholar 

Jiang L, Chen W, Dong B, Mei K, Zhu C, Liu J, Gai M, Yan Y, Wang G, Zuo L, Shi H (2021) A deep learning-based approach for glomeruli instance segmentation from multistained renal biopsy pathologic images. Am J Pathol 191(8):1431–1441

Article  PubMed  Google Scholar 

Cao G, Song W, Zhao Z (2019) Gastric cancer diagnosis with mask R-CNN. In: 2019 11th international conference on intelligent human-machine systems and cybernetics (IHMSC), IEEE, Vol. 1, pp 60–63

Zafar MM, Rauf Z, Sohail A, Khan AR, Obaidullah M, Khan SH, Lee YS, Khan A (2022) Detection of tumour infiltrating lymphocytes in CD3 and CD8 stained histopathological images using a two-phase deep CNN. Photodiagn Photodyn Ther 37:102676

Article  CAS  Google Scholar 

Zhang J, Zhang Y, Zhu S, Xu X (2020) Constrained multi-scale dense connections for accurate biomedical image segmentation. In: 2020 IEEE international conference on bioinformatics and biomedicine (BIBM), IEEE, pp 877–884

Yi J, Wu P, Huang Q, Qu H, Hoeppner DJ, Metaxas DN (2019) Context-refined neural cell instance segmentation. In: 2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019), IEEE, pp 1028–1032

Cheng Z, Qu A (2020) A fast and accurate algorithm for nuclei instance segmentation in microscopy images. IEEE Access 8:158679–158689

Article  Google Scholar 

Li K, Qian Z, Han Y, Eric I, Chang C, Wei B, Lai M, Liao J, Fan Y, Xu Y (2023) Weakly supervised histopathology image segmentation with self-attention. Med Image Anal 86:102791

Article  PubMed  Google Scholar 

He Q, He L, Duan H, Sun Q, Zheng R, Guan J, He Y, Huang W, Guan T (2023) Expression site agnostic histopathology image segmentation framework by self supervised domain adaption. Comput Biol Med 152:106412

Article  PubMed  CAS  Google Scholar 

Nadarajan G, Doyle S (2021) Conditional generative adversarial networks for h&e to if domain transfer: experiments with breast and prostate cancer. In: Medical imaging 2021: digital pathology, SPIE, Vol. 11603, pp 144–154

Chen Z, Yu W, Wong IH, Wong TT (2021) Deep-learning-assisted microscopy with ultraviolet surface excitation for rapid slide-free histological imaging. Biomed Opt Express 12(9):5920–5938

Article  PubMed  PubMed Central  CAS  Google Scholar 

Govind D, Santo BA, Ginley B, Yacoub R, Rosenberg AZ, Jen KY, Walavalkar V, Wilding GE, Worral AM, Mohammad I, Sarder, P (2021) Automated detection and quantification of Wilms’ tumor 1-positive cells in murine diabetic kidney disease. In: Medical imaging 2021: digital pathology, SPIE, Vol. 11603, pp 76–82

Salehi P, Chalechale A (2020) Pix2pix-based stain-to-stain translation: A solution for robust stain normalization in histopathology images analysis. In: 2020 international conference on machine vision and image processing (MVIP), IEEE, pp 1–7

Huang M, Wang T, Cai Y, Fan H, Li Z (2023) StainGAN: Learning a structural preserving translation for white blood cell images. J Biophotonics 16(11):e202300196

Article  PubMed  CAS  Google Scholar 

Ghahremani P, Li Y, Kaufman A, Vanguri R, Greenwald N, Angelo M, Hollmann TJ, Nadeem S (2022) Deep learning-inferred multiplex immunofluorescence for immunohistochemical image quantification. Nat Mach Intell 4(4):401–412

Article  PubMed  PubMed Central  Google Scholar 

Berijanian M, Schaadt NS, Huang B, Lotz J, Feuerhake F, Merhof D (2023) Unsupervised many-to-many stain translation for histological image augmentation to improve classification accuracy. J Pathol Inform 14:100195

Article  PubMed  PubMed Central  Google Scholar 

Yan R, He Q, Liu Y, Ye P, Zhu L, Shi S, Gou J, He Y, Guan T, Zhou G (2023) Unpaired virtual histological staining using prior-guided generative adversarial networks. Comput Med Imaging Graph 105:102185

Article  PubMed  Google Scholar 

Teramoto A, Yamada A, Tsukamoto T, Kiriyama Y, Sakurai E, Shiogama K, Michiba A, Imaizumi K, Saito K, Fujita H (2021) Mutual stain conversion between Giemsa and Papanicolaou in cytological images using cycle generative adversarial network. Heliyon 7(2):e06331

Article  PubMed  PubMed Central  Google Scholar 

Dimitri GM, Andreini P, Bonechi S, Bianchini M, Mecocci A, Scarselli F, Zacchi A, Garosi G, Marcuzzo T, Tripodi SA (2022) Deep learning approaches for the segmentation of glomeruli in kidney histopathological images. Mathematics 10(11):1934

Article  Google Scholar 

Gu Y, Ruan R, Yan Y, Zhao J, Sheng W, Liang L, Huang B (2022) Glomerulus semantic segmentation using ensemble of deep learning models. Arab J Sci Eng 47(11):14013–14024

Article  Google Scholar 

Rehem JMC, dos Santos WLC, Duarte AA, de Oliveira LR, Angelo MF (2021) Automatic glomerulus detection in renal histological images. In: Medical imaging 2021: digital pathology, SPIE, Vol. 11603, pp 115–125

Meng Z, Chen SJ, Lyu T, Zhang Z, Wang X, Sheng B, Mao L (2021) Recognition and classification of glomerular pathological images based on deep learning. J Comput-Aid Des Comput Graph 33(6):947–955

Google Scholar 

Liu Y, Wang J (2021) FEU-Net: Glomeruli region segmentation network based on pseudo-labelling and channel attention mechanisms. In: International conference on image processing and intelligent control (IPIC 2021), SPIE, Vol. 11928, pp 41–51

Li J, He Q, Liu Y, Wang Y, Guan T, Ye J, He Y, Wang Z (2023) Glomerular lesion recognition based on pathology images with annotation noise via noisy label learning. IEEE Access

Gadermayr M, Dombrowski AK, Klinkhammer BM, Boor P, Merhof D (2019) CNN cascades for segmenting sparse objects in gigapixel whole slide images. Comput Med Imaging Graph 71:40–48

Article  PubMed  Google Scholar 

Hermsen M, de Bel T, Den Boer M, Steenbergen EJ, Kers J, Florquin S, Roelofs Joris JTH, Stegall MD, Alexander MP, Smith BH, Smeets B, Hilbrands LB, van der Laak JA (2019) Deep learning–based histopathologic assessment of kidney tissue. J Am Soc Nephrol 30(10):1968

Article  PubMed  PubMed Central  Google Scholar 

Bueno G, Fernandez-Carrobles MM, Gonzalez-Lopez L, Deniz O (2020) Glomerulosclerosis identification in whole slide images using semantic segmentation. Comput Methods Programs Biomed 184:105273

Article  PubMed  Google Scholar 

Kannan S, Morgan LA, Liang B, Cheung MG, Lin CQ, Mun D, Nader RG, Belghasem ME, Henderson JM, Francis JM, Chitalia VC, Kolachalama VB (2019) Segmentation of glomeruli within trichrome images using deep learning. Kid Int Rep 4(7):955–962

Google Scholar 

Uchino E, Suzuki K, Sato N, Kojima R, Tamada Y, Hiragi S, Yokoi H, Yugami N, Minamiguchi S, Haga H, Yanagita M, Okuno Y (2020) Classification of glomerular pathological findings using deep learning and nephrologist–AI collective intelligence approach. Int J Med Inform 141:104231

Article  PubMed  Google Scholar 

Barros GO, Navarro B, Duarte A, Dos-Santos WL (2017) PathoSpotter-K: a computational tool for the automatic identification of glomerular lesions in histological images of kidneys. Sci Rep 7(1):46769

Article  PubMed  PubMed Central  Google Scholar 

Zeng C, Nan Y, Xu F, Lei Q, Li F, Chen T, Liang S, Hou X, Lv B, Liang D, Luo W, Lv C, Li X, Xie G, Liu Z (2020) Identification of glomerular lesions and intrinsic glomerular cell types in kidney diseases via deep learning. J Pathol 252(1):53–64

Article  PubMed  Google Scholar 

Howard A, Lawrence A, Sims B, Tinsley E,Kazmierczak J, Borner K, Godwin, Novaes M, Culliton P,Holland R, Watson R, Ju Y (2020) HuBMAP - Hacking the Kidney. Kaggle. https://kaggle.com/competitions/hubmap-kidney-segmentation. Accessed 7 July 2023

Park T, Efros AA, Zhang R, Zhu JY (2020) Contrastive learning for unpaired image-to-image translation. In: Computer vision–ECCV 2020: 16th European conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part IX 16, Springer International Publishing, pp 319–345

He K, Gkioxari G, Dollár P, Girshick R (2017) Mask r-cnn. In: Proceedings of the IEEE international conference on computer vision, pp 2961–2969

Liu Z, Lin Y, Cao Y, Hu H, Wei Y, Zhang Z, Stephen L, Guo B (2021) Swin transformer: Hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE/CVF international conference on computer vision, pp 10012–10022