[1] C. He, H. He, J. Chang, B. Chen, H. Ma, M. J. Booth. Polarisation optics for biomedical and clinical applications: A review. Light: Sci. Appl., 10, 194(2021).
[2] N. Ghosh, I. A. Vitkin. Tissue polarimetry: Concepts, challenges, applications, and outlook. J. Biomed. Opt., 16, 110801(2011).
[3] H. He, R. Liao, N. Zeng, P. Li, Z. Chen, X. Liu, H. Ma. Mueller matrix polarimetry — an emerging new tool for characterizing the microstructural feature of complex biological specimen. J. Lightwave Technol., 37, 2534-2548(2018).
[4] J. Qi, D. S. Elson. Mueller polarimetric imaging for surgical and diagnostic applications: A review. J. Biophotonics, 10, 950-982(2017).
[5] J. C. Ramella-Roman, I. Saytashev, M. Piccini. A review of polarization-based imaging technologies for clinical and preclinical applications. J. Opt., 22, 123001(2020).
[6] V. V. Tuchin. Polarized light interaction with tissues. J. Biomed. Opt., 21, 071114(2016).
[7] C. He, J. Chang, P. S. Salter et al. Revealing complex optical phenomena through vectorial metrics. Adv. Photonics, 4, 026001(2022).
[8] Y. Shen, R. Huang, H. He, S. Liu, Y. Dong, J. Wu, H. Ma. Comparative study of the influence of imaging resolution on linear retardance parameters derived from the mueller matrix. Biomed. Opt. Express, 12, 211-225(2021).
[9] W. E. Baylis, J. Bonenfant, J. Derbyshire, J. Huschilt. Light polarization: A geometricalgebra approach. Am. J. Phys., 61, 534-545(1993).
[10] H. Jerrard. Modern description of polarized light: Matrix methods. Opt. Laser Technol., 14, 309-319(1982).
[11] D. Layden, N. Ghosh, I. A. Vitkin. Quantitative polarimetry for tissue characterization and diagnosis. Adv. Biophotonics: Tissue Opt. Sectioning, 5, 73-108(2013).
[12] Y. Yao, J. Wan, F. Zhang, Y. Dong, L. Chen, H. Ma. Correlation of image textures of a polarization feature parameter and the microstructures of liver fibrosis tissues. J. Innov. Opt. Health Sci., 16, 2241004(2023).
[13] E. Du, H. He, N. Zeng, M. Sun, Y. Guo, J. Wu, S. Liu, H. Ma. Mueller matrix polarimetry for differentiating characteristic features of cancerous tissues. J. Biomed. Opt., 19, 076013(2014).
[14] M. Dubreuil, P. Babilotte, L. Martin, D. Sevrain, S. Rivet, Y. Le Grand, G. Le Brun, B. Turlin, B. Le Jeune. Mueller matrix polarimetry for improved liver fibrosis diagnosis. Opt. Lett., 37, 1061-1063(2012).
[15] C. He, J. Chang, Q. Hu et al. Complex vectorial optics through gradient index lens cascades. Nat. Commun., 10, 4264(2019).
[16] I. Ahmad, M. Ahmad, K. Khan, S. Ashraf, S. Ahmad, M. Ikram. Ex vivo characterization of normal and adenocarcinoma colon samples by Mueller matrix polarimetry. J. Biomed. Opt., 20, 056012(2015).
[17] D. Ivanov, V. Dremin, E. Borisova, A. Bykov, T. Novikova, I. Meglinski, R. Ossikovski. Polarization and depolarization metrics as optical markers in support to histopathology of ex vivo colon tissue. Biomed. Opt. Express, 12, 4560-4572(2021).
[18] T. Liu, M. Lu, B. Chen, Q. Zhong, J. Li, H. He, H. Mao, H. Ma. Distinguishing structural features between crohn’s disease and gastrointestinal luminal tuberculosis using Mueller matrix derived parameters. J. Biophotonics, 12, e201900151(2019).
[19] T. Novikova, A. Pierangelo, S. Manhas, A. Benali, P. Validire, B. Gayet, A. De Martino. The origins of polarimetric image contrast between healthy and cancerous human colon tissue. Appl. Phys. Lett., 102, 241103(2013).
[20] A. Pierangelo, S. Manhas, A. Benali, C. Fallet, J. L. Totobenazara, M. R. Antonelli, T. Novikova, B. Gayet, A. De Martino, P. Validire. Multispectral Mueller polarimetric imaging detecting residual cancer and cancer regression after neoadjuvant treatment for colorectal carcinomas. J. Biomed. Opt., 18, 046014(2013).
[21] A. Pierangelo, A. Nazac, A. Benali, P. Validire, H. Cohen, T. Novikova, B. H. Ibrahim, S. Manhas, C. Fallet, M. R. Antonelli. Polarimetric imaging of uterine cervix: A case study. Opt. Express, 21, 14120-14130(2013).
[22] Y. Wang, H. He, J. Chang, N. Zeng, S. Liu, M. Li, H. Ma. Differentiating characteristic microstructural features of cancerous tissues using Mueller matrix microscope. Micron, 79, 8-15(2015).
[23] L. Deng, C. Chen, W. Yu, C. Shao, Z. Shen, Y. Wang, C. He, H. Li, Z. Liu, H. He. Influence of hematoxylin and eosin staining on linear birefringence measurement of fibrous tissue structures in polarization microscopy. J. Biomed. Opt., 28, 102909(2023).
[24] B. Bai, X. Yang, Y. Li, Y. Zhang, N. Pillar, A. Ozcan. Deep learning-enabled virtual histological staining of biological samples. Light: Sci. Appl., 12, 57(2023).
[25] Y. Rivenson, H. Wang, Z. Wei, K. de Haan, Y. Zhang, Y. Wu, H. Günaydın, J. E. Zuckerman, T. Chong, A. E. Sisk. Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning. Nat. Biomed. Eng., 3, 466-477(2019).
[26] Y. Rivenson, T. Liu, Z. Wei, Y. Zhang, K. de Haan, A. Ozcan. Phasestain: The digital staining of label-free quantitative phase microscopy images using deep learning. Light: Sci. Appl., 8, 23(2019).
[27] L. Si, N. Li, T. Huang, S. Du, Y. Dong, Y. Yao, H. Ma. Computational image translation from Mueller matrix polarimetry to bright-field microscopy. J. Biophotonics, 15, e202100242(2022).
[28] D. B. Chenault, J. L. Pezzaniti, R. A. Chipman. Mueller matrix algorithms. Proc. SPIE, 1746, 231-246(1992).
[29] J. Zhou, H. He, Z. Chen, Y. Wang, H. Ma. Modulus design multiwavelength polarization microscope for transmission Mueller matrix imaging. J. Biomed. Opt., 23, 016007(2018).
[30] T. Xuan, H. Zhai, H. He, C. He, S. Liu, H. Ma. Self-registration of constant-step rotating Mueller matrix polarimeters. Opt. Lett., 47, 5797-5800(2022).
[31] L. E. Brouwer. Beweis der invarianz des n-dimensionalen gebiets. Math. Ann., 71, 305-313(1911).
[32] R. Bro, A. K. Smilde. Principal component analysis. Anal. Methods, 6, 2812-2831(2014).
[33] T. A. A. Tosta, P. R. de Faria, L. A. Neves, M. Z. Nascimento. Computational normalization of H&E-stained histological images: Progress, challenges and future potential. Artif. Intell. Med., 95, 118-132(2019).
[34] A. Vahadane, T. Peng, A. Sethi, S. Albarqouni, L. Wang, M. Baust, K. Steiger, A. M. Schlitter, I. Esposito, N. Navab. Structure-preserving color normalization and sparse stain separation for histological images. IEEE Trans. Med. Imag., 35, 1962-1971(2016).
[35] J. Y. Zhu, T. Park, P. Isola, A. A. Efros. Unpaired image-to-image translation using cycle-consistent adversarial networks, 2223-2232(2017).
[36] H. Zhao, O. Gallo, I. Frosio, J. Kautz. Loss functions for neural networks for image processing.
[37] S. Kolhar, J. Jagtap. Convolutional neural network based encoder-decoder architectures for semantic segmentation of plants. Ecol. Inform., 64, 101373(2021).
[38] T. Tong, G. Li, X. Liu, Q. Gao. Image superresolution using dense skip connections, 4799-4807(2017).
[39] Y. Chen, H. Jiang, C. Li, X. Jia, P. Ghamisi. Deep feature extraction and classification of hyperspectral images based on convolutional neural networks. IEEE Trans. Geosci. Remote Sens., 54, 6232-6251(2016).
[40] S. Bock, M. Weiß. A proof of local convergence for the adam optimizer, 1-8(2019).
[41] N. Shazeer, M. Stern. Adafactor: Adaptive learning rates with sublinear memory cost, 4596-4604(2018).
[42] B. Eysenbach, R. R. Salakhutdinov, S. Levine. Search on the replay buffer: Bridging planning and reinforcement learning. Adv. Neural Inf. Process. Syst., 32, 15246-15257(2019).
[43] E. Karami, S. Prasad, M. Shehata. Image matching using sift, surf, brief and orb: Performance comparison for distorted images.
[44] Y. Biadgie, K.-A. Sohn. Feature detector using adaptive accelerated segment test, 1-4(2014).
[45] M. Calonder, V. Lepetit, C. Strecha, P. Fua. Brief: Binary robust independent elementary features. Proceedings, Part IV 11, Crete, Greece, 778-792(2010).
[46] M. P. Sampat, Z. Wang, S. Gupta, A. C. Bovik, M. K. Markey. Complex wavelet structural similarity: A new image similarity index. IEEE Trans. Image Process., 18, 2385-2401(2009).
[47] J. Korhonen, J. You. Peak signal-to-noise ratio evisited: Is simple beautiful?, 37-38(2012).