Application of quantitative histomorphometric features in computational pathology

Abstract

Computer vision has facilitated the execution of various computer-aided diagnostic tasks. From a methodological perspective, these tasks are primarily implemented using two dominant strategies: end-to-end Deep learning (DL)-based methods and traditional feature engineering-based methods. DL methods are capable of automatically extracting, analyzing, and filtering features, leading to final decision-making from whole slide images. However, these methods are often criticized for the “black box” issue, a significant limitation of DL. In contrast, traditional feature engineering-based methods involve well-defined quantitative input features. But it was considered as less potent than DL methods. Advances in segmentation technology and the development of quantitative histomorphometric (QH) feature representation have propelled the evolution of feature engineering-based methods. This review contrasts the performance differences between the two methods and traces the development of QH feature representation. The conclusion is that, with the ongoing progress in QH feature representation and segmentation technology, methods based on QH features will leverage their advantages— such as explainability, reduced reliance on large training datasets, and lower computational resource requirements—to play a more significant role in some clinical tasks. They may even replace DL methods somewhat or be used in conjunction with them to achieve accurate and understandable results.

Keywords

deep learning / pathological image / quantitative histomorphometric feature / segmentation

References

[1] J. K. Chan, Int. J. Surg. Pathol. 2014, 22, 12.

[2] M. Cui, D. Y. Zhang, Lab. Invest. 2021, 101, 412.

[3] J. Bouvrie, Notes on convolutional neural networks, Citeseer, New Jersey, USA 2006. https://web.mit.edu/jvb/www/papers/cnn_tutorial.pdf

[4] Z. Zhang, P. Cui, W. Zhu, IEEE Trans. Knowl. Data Eng. 2020, 34, 249.

[5] A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, I. Polosukhin, in Proceedings of the 31st International Conference on Neural Information Processing Systems, Curran Associates Inc., Long Beach, California, USA 2017, pp. 6000–6010.

[6] T. Araújo, G. Aresta, E. Castro, J. Rouco, P. Aguiar, C. Eloy, A. Polónia, A. Campilho, PLoS One 2017, 12, e0177544.

[7] M. Šarić, M. Russo, M. Stella, M. Sikora, in 2019 4th International Conference on Smart and Sustainable Technologies (SpliTech), IEEE, Split, Croatia 2019, pp. 1–4.

[8] G. Litjens, C. I. Sanchez, N. Timofeeva, M. Hermsen, I. Nagtegaal, I. Kovacs, C. Hulsbergen-van de Kaa, P. Bult, B. van Ginneken, J. van der Laak, Sci. Rep. 2016, 6, 26286.

[9] H. Fu, W. Mi, B. Pan, Y. Guo, J. Li, R. Xu, J. Zheng, C. Zou, T. Zhang, Z. Liang, J. Zou, H. Zou, Front. Oncol. 2021, 11, 665929.

[10] C. Rudin, Nat. Mach. Intell. 2019, 1, 206.

[11] G. Lee, S. Ali, R. Veltri, J. I. Epstein, C. Christudass, A. Madabhush, in Medical Image Computing Computer-Assisted Intervention–MICCAI 2013, Vol. 8151. (Eds: K. Mori, I. Sakuma, Y. Sato, C. Barillot, N. Navab), Springer, Berlin, Heidelberg 2013, pp. 396–403.

[12] J. Fox, G. Monetee, R and S-Plus Companion to Applied Regression, Sage Publications Inc., USA 2002.

[13] V. V. Belle, K. Pelckmans, S. V. Huffel, J. A. K. Suykens, Artificial Intelligence in Medicine 2011, 52, 107.

[14] H. Ishwaran, U. B. Kogalur, E. H. Blackstone, M. S. Lauer, Ann. Appl. Stat. 2008, 2, 841.

[15] R. R. Rawat, D. Ruderman, P. Macklin, D. L. Rimm, D. B. Agus, NPJ Breast Cancer 2018, 4, 32.

[16] Y. Zhdanovich, J. Ackermann, P. J. Wild, J. Kollermann, K. Bankov, C. Doring, N. Flinner, H. Reis, M. Wenzel, B. Hoh, P. Mandel, T. J. Vogl, P. Harter, K. Filipski, I. Koch, S. Bernatz, BMC Bioinf. 2023, 24, 1.

[17] P. Strom, K. Kartasalo, H. Olsson, L. Solorzano, B. Delahunt, D. M. Berney, D. G. Bostwick, A. J. Evans, D. J. Grignon, P. A. Humphrey, K. A. Iczkowski, J. G. Kench, G. Kristiansen, T. H. van der Kwast, K. R. M. Leite, J. K. McKenney, J. Oxley, C. C. Pan, H. Samaratunga, J. R. Srigley, H. Takahashi, T. Tsuzuki, M. Varma, M. Zhou, J. Lindberg, C. Lindskog, P. Ruusuvuori, C. Wahlby, H. Gronberg, M. Rantalainen, L. Egevad, M. Eklund, Lancet Oncol. 2020, 21, 222.

[18] S. Doyle, M. Hwang, K. Shah, A. Madabhushi, M. Feldman, J. Tomaszeweski, in 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, IEEE, Arlington, VA, USA 2007, pp. 1284–1287.

[19] J. Ren, E. Sadimin, D. J. Foran, X. Qi, in Medical Imaging 2017: Image Processing Vol. 10133 (Eds: M. A. Styner, E. D. Angelini), SPIE, Orlando, Florida, United States 2017, p. 101331V.

[20] C. Yan, K. Nakane, X. Wang, Y. Fu, H. Lu, X. Fan, M. D. Feldman, A. Madabhushi, J. Xu, Comput. Methods Programs Biomed. 2020, 194, 105528.

[21] W. Bulten, H. Pinckaers, H. van Boven, R. Vink, T. de Bel, B. van Ginneken, J. van der Laak, C. Hulsbergen-van de Kaa, G. Litjens, Lancet Oncol. 2020, 21, 233.

[22] P. Leo, A. Janowczyk, R. Elliott, N. Janaki, K. Bera, R. Shiradkar, X. Farre, P. Fu, A. El-Fahmawi, M. Shahait, J. Kim, D. Lee, K. Yamoah, T. R. Rebbeck, F. Khani, B. D. Robinson, L. Eklund, I. Jambor, H. Merisaari, O. Ettala, P. Taimen, H. J. Aronen, P. J. Bostrom, A. Tewari, C. Magi-Galluzzi, E. Klein, A. Purysko, N. Nc Shih, M. Feldman, S. Gupta, P. Lal, A. Madabhushi, npj Precis. Oncol. 2021, 5, 35.

[23] E. Dietrich, P. Fuhlert, A. Ernst, G. Sauter, M. Lennartz, H. S. Stiehl, M. Zimmermann, S. Bonn, Proc. Machine Learn. Res. 2021, 158, 38.

[24] S. Chandramouli, P. Leo, G. Lee, R. Elliott, C. Davis, G. Zhu, P. Fu, J. I. Epstein, R. Veltri, A. Madabhushi, Cancers 2020, 12, 2708.

[25] P. Gamble, R. Jaroensri, H. Wang, F. Tan, M. Moran, T. Brown, I. Flament-Auvigne, E. A. Rakha, M. Toss, D. J. Dabbs, P. Regitnig, N. Olson, J. H. Wren, C. Robinson, G. S. Corrado, L. H. Peng, Y. Liu, C. H. Mermel, D. F. Steiner, P. C. Chen, Commun. Med. 2021, 1, 14.

[26] Y. Chen, H. Li, A. Janowczyk, P. Toro, G. Corredor, J. Whitney, C. Lu, C. F. Koyuncu, M. Mokhtari, C. Buzzy, S. Ganesan, M. D. Feldman, P. Fu, H. Corbin, A. Harbhajanka, H. Gilmore, L. J. Goldstein, N. E. Davidson, S. Desai, V. Parmar, A. Madabhushi, NPJ Breast Cancer 2023, 9, 40.

[27] R. Albusayli, J. D. Graham, N. Pathmanathan, M. Shaban, S. E. A. Raza, F. Minhas, J. E. Armes, N. Rajpoot, J. Pathol. 2023, 260, 32.

[28] R. J. Chen, M. Y. Lu, M. Shaban, C. Chen, T. Y. Chen, D. F. K. Williamson, F. Mahmood, in Medical Image Computing and Computer Assisted Intervention–MICCAI 2021, Vol. 12908 (Eds: M. de Bruijne, P. C. Cattin, S. Cotin, N. Padoy, S. Speidel, Y. Zheng, C. Essert), Springer, Cham 2021, pp. 339–349.

[29] Z. Wang, Q. Gao, X. Yi, X. Zhang, Y. Zhang, D. Zhang, P. Liò, C. Bain, R. Bassed, S. Li, Y. Guo, S. Imoto, J. Yao, R. J. Daly, J. Song, Comput. Methods Programs Biomed. 2023, 241, 107733.

[30] S. Jiang, A. A. Suriawinata, S. Hassanpour, Comput. Biol. 2023, 158, 106883.

[31] Z. Shao, Y. Chen, H. Bian, J. Zhang, G. Liu, Y. Zhang, in Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37 (Eds: B. Williams, Y. Chen, J. Neville), AAAI Press, Washington, DC, USA 2023, pp. 2209–2217.

[32] R. Turkki, D. Byckhov, M. Lundin, J. Isola, S. Nordling, P. E. Kovanen, C. Verrill, K. von Smitten, H. Joensuu, J. Lundin, N. Linder, Breast Cancer Res. Treat. 2019, 177, 41.

[33] J. Whitney, G. Corredor, A. Janowczyk, S. Ganesan, S. Doyle, J. Tomaszewski, M. Feldman, H. Gilmore, A. Madabhushi, BMC Cancer 2018, 18, 610.

[34] Y. Shi, L. T. Olsson, K. A. Hoadley, B. C. Calhoun, J. Marron, J. Geradts, M. Niethammer, M. A. Troester, NPJ Breast Cancer 2023, 9, 92.

[35] B. Shen, A. Saito, A. Ueda, K. Fujita, Y. Nagamatsu, M. Hashimoto, M. Kobayashi, A. H. Mirza, H. P. Graf, E. Cosatto, S. Hazama, H. Nagano, E. Sato, J. Matsubayashi, T. Nagao, E. Cheng, S. A. Hoda, T. Ishikawa, M. Kuroda, J. Pathol. Clin. Res. 2023, 9, 182.

[36] X. Luo, S. Yin, L. Yang, J. Fujimoto, Y. Yang, C. Moran, N. Kalhor, A. Weissferdt, Y. Xie, A. Gazdar, J. Minna, I. I. Wistuba, Y. Mao, G. Xiao, Sci. Rep. 2019, 9, 6886.

[37] C. Lu, K. Bera, X. Wang, P. Prasanna, J. Xu, A. Janowczyk, N. Beig, M. Yang, P. Fu, J. Lewis, H. Choi, R. A. Schmid, S. Berezowska, K. Schalper, D. Rimm, V. Velcheti, A. Madabhushi, Lancet Digit. Health 2020, 2, e594.

[38] T. Qaiser, C. Y. Lee, M. Vandenberghe, J. Yeh, M. A. Gavrielides, J. Hipp, M. Scott, J. Reischl, npj Precis. Oncol. 2022, 6, 37.

[39] C. Lu, C. Koyuncu, G. Corredor, P. Prasanna, P. Leo, X. Wang, A. Janowczyk, K. Bera, J. Lewis, Jr., V. Velcheti, A. Madabhushi, Med. Image Anal. 2021, 68, 101903.

[40] X. Wang, C. Barrera, K. Bera, V. S. Viswanathan, S. Azarianpour-Esfahani, C. Koyuncu, P. Velu, M. D. Feldman, M. Yang, P. Fu, K. A. Schalper, H. Mahdi, C. Lu, V. Velcheti, A. Madabhushi, Sci. Adv. 2022, 8, eabn3966.

[41] C. Barrera, G. Corredor, V. S. Viswanathan, R. Ding, P. Toro, P. Fu, C. Buzzy, C. Lu, P. Velu, P. Zens, S. Berezowska, M. Belete, D. Balli, H. Chang, V. Baxi, K. Syrigos, D. L. Rimm, V. Velcheti, K. Schalper, E. Romero, A. Madabhushi, npj Precis. Oncol. 2023, 7, 52.

[42] B. Li, L. Yang, H. Zhang, H. Li, C. Jiang, Y. Yao, S. Cheng, B. Zou, B. Fan, T. Dong, Mod. Pathol. 2023, 36, 100208.

[43] J. Hu, C. Cui, W. Yang, L. Huang, R. Yu, S. Liu, Y. Kong, Transl. Oncol. 2021, 14, 100921.

[44] Y. Zhang, Z. Yang, R. Chen, Y. Zhu, L. Liu, J. Dong, Z. Zhang, X. Sun, J. Ying, D. Lin, L. Yang, M. Zhou, NPJ Digit. Med. 2024, 7, 15.

[45] R. L. Siegel, A. N. Giaquinto, A. Jemal, CA Cancer J. Clin. 2024, 74, 12.

[46] S. A. Dudani, IEEE Trans. Syst. Man, Cybernetics 1976, SMC-6, 325.

[47] J. J. Dignam, D. A. Hamstra, H. Lepor, D. Grignon, H. Brereton, A. Currey, S. Rosenthal, K. L. Zeitzer, V. M. Venkatesan, E. M. Horwitz, J. Clin. Oncol. 2019, 37, 213.

[48] X. Zhu, J. Yao, J. Huang, in 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE, Shenzhen, China 2016, pp. 544–547.

[49] L. Xiao, J.-G. Yu, Z. Liu, J. Ou, S. Deng, Z. Yang, Y. Li, in Proceedings of Medical Image Computing and Computer Assisted Intervention–MICCAI 2020:23rd International Conference, Lima, Peru 2020, pp. 449–458.

[50] D. Kumar, B. J. R. E. Klefsjö, Reliab. Eng. Syst. Saf. 1994, 44, 177.

[51] P. A. Gutiérrez, M. Perez-Ortiz, J. Sanchez-Monedero, F. Fernandez-Navarro, C. Hervas-Martinez, IEEE Trans. Knowl. Data Eng. 2015, 28, 127.

[52] G. Huang, Z. Liu, L. Van Der Maaten, K. Q. Weinberger, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pp. 4700–4708.

[53] Early Breast Cancer Trialists’Collaborative Group, Lancet Oncol. 1998, 351, 1451.

[54] C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, Z. Wojna, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016, pp. 2818–2826.

[55] K. He, X. Zhang, S. Ren, J. Sun, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016, pp. 770–778.

[56] R. Li, J. Yao, X. Zhu, Y. Li, J. Huang, in Medical Image Computing and Computer Assisted Intervention–MICCAI 2018, Vol. 11071 (Eds: A. Frangi, J. Schnabel, C. Davatzikos, C. Alberola-López, G. Fichtinger), Springer, Cham 2018, pp. 174–182.

[57] S. Paik, S. Shak, G. Tang, C. Kim, J. Baker, M. Cronin, F. L. Baehner, M. G. Walker, D. Watson, T. Park, N. Engl. J. Med. 2004, 351, 2817.

[58] J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, L. Fei-Fei, in 2009 IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Miami, FL, USA 2009, pp. 248–255.

[59] A. Krizhevsky, I. Sutskever, G. E. Hinton, Commun. ACM 2017, 60, 84.

[60] K. Simonyan, A. Zisserman, (Preprint) arXiv:1409.1556v6, v6, 2015.

[61] H. Guan, M. Liu, in IEEE Transactions on Biomedical Engineering, Vol. 69, IEEE 2022, pp. 1173–1185.

[62] R. M. Haralick, K. Shanmugam, I. H. Dinstein, in IEEE Transactions on Systems, Man, and Cybernetics, Vol. SMC-3, IEEE 1973, pp. 610–621.

[63] Y. Wang, X. Pan, H. Lin, C. Han, Y. An, B. Qiu, Z. Feng, X. Huang, Z. Xu, Z. Shi, X. Chen, B. Li, L. Yan, C. Lu, Z. Li, Y. Cui, Z. Liu, Z. Liu, J. Transl. Med. 2022, 20, 595.

[64] H. Sharma, N. Zerbe, I. Klempert, O. Hellwich, P. Hufnagl, Comput. Med. Imaging Graph 2017, 61, 2.

[65] Y. Yasuda, K. Tokunaga, T. Koga, C. Sakamoto, I. G. Goldberg, N. Saitoh, M. Nakao, Cancer Med. 2020, 9, 2223.

[66] S. Reis, P. Gazinska, J. H. Hipwell, T. Mertzanidou, K. Naidoo, N. Williams, S. Pinder, D. J. Hawkes, in IEEE Transactions on Biomedical Engineering, Vol. 64, IEEE 2017, pp. 2344–2352.

[67] L. Langer, Y. Binenbaum, L. Gugel, M. Amit, Z. Gil, S. Dekel, Int. J. Comput. Assist. Radiol. Surg. 2015, 10, 1043.

[68] J. A. Diao, J. K. Wang, W. F. Chui, V. Mountain, S. C. Gullapally, R. Srinivasan, R. N. Mitchell, B. Glass, S. Hoffman, S. K. Rao, C. Maheshwari, A. Lahiri, A. Prakash, R. McLoughlin, J. K. Kerner, M. B. Resnick, M. C. Montalto, A. Khosla, I. N. Wapinski, A. H. Beck, H. L. Elliott, A. Taylor-Weiner, Nat. Commun. 2021, 12, 1613.

[69] T. de Bel, G. Litjens, J. Ogony, M. Stallings-Mann, J. M. Carter, T. Hilton, D. C. Radisky, R. A. Vierkant, B. Broderick, T. L. Hoskin, S. J. Winham, M. H. Frost, D. W. Visscher, T. Allers, A. C. Degnim, M. E. Sherman, J. van der Laak, NPJ Breast Cancer 2022, 8, 13.

[70] M. E. Sherman, T. de Bel, M. G. Heckman, L. J. White, J. Ogony, M. Stallings-Mann, T. Hilton, A. C. Degnim, R. A. Vierkant, T. Hoskin, M. R. Jensen, L. Pacheco-Spann, J. E. Henry, A. M. Storniolo, J. M. Carter, S. J. Winham, D. C. Radisky, J. van der Laak, Breast Cancer Res. Treat. 2022, 194, 149.

[71] N. Ing, F. Huang, A. Conley, S. You, Z. Ma, S. Klimov, C. Ohe, X. Yuan, M. B. Amin, R. Figlin, A. Gertych, B. S. Knudsen, Sci. Rep. 2017, 7, 13190.

[72] M. Y. Ji, L. Yuan, S. M. Lu, M. T. Gao, Z. Zeng, N. Zhan, Y. J. Ding, Z. R. Liu, P. X. Huang, C. Lu, W. G. Dong, J. Transl. Med. 2020, 18, 129.

[73] W. Xie, N. P. Reder, C. Koyuncu, P. Leo, S. Hawley, H. Huang, C. Mao, N. Postupna, S. Kang, R. Serafin, G. Gao, Q. Han, K. W. Bishop, L. A. Barner, P. Fu, J. L. Wright, C. D. Keene, J. C. Vaughan, A. Janowczyk, A. K. Glaser, A. Madabhushi, L. D. True, J. T. C. Liu, Cancer Res. 2022, 82, 334.

[74] C. Lu, D. Romo-Bucheli, X. Wang, A. Janowczyk, S. Ganesan, H. Gilmore, D. Rimm, A. Madabhushi, Lab. Invest. 2018, 98, 1438.

[75] F. Martino, S. Varricchio, D. Russo, F. Merolla, G. Ilardi, M. Mascolo, G. O. dell’Aversana, L. Califano, G. Toscano, G. De Pietro, Cancers 2020, 12, 1344.

[76] K. H. Yu, G. J. Berry, D. L. Rubin, C. Re, R. B. Altman, M. Snyder, Cell Syst. 2017, 5, 620.

[77] H. Liao, T. Xiong, J. Peng, L. Xu, M. Liao, Z. Zhang, Z. Wu, K. Yuan, Y. Zeng, Ann. Surg Oncol. 2020, 27, 2359.

[78] M. Y. Ji, L. Yuan, X. D. Jiang, Z. Zeng, N. Zhan, P. X. Huang, C. Lu, W. G. Dong, J. Transl. Med. 2019, 17, 92.

[79] X. Wang, K. Bera, C. Barrera, Y. Zhou, C. Lu, P. Vaidya, P. Fu, M. Yang, R. A. Schmid, S. Berezowska, H. Choi, V. Velcheti, A. Madabhushi, eBioMedicine 2021, 69, 103481.

[80] J. E. Verdone, P. Parsana, R. W. Veltri, K. J. Pienta, Prostate 2015, 75, 218.

[81] S. Doyle, M. D. Feldman, N. Shih, J. Tomaszewski, A. Madabhushi, BMC Bioinform 2012, 13, 282.

[82] S. Wang, R. Rong, D. M. Yang, J. Fujimoto, J. A. Bishop, S. Yan, L. Cai, C. Behrens, L. D. Berry, C. Wilhelm, D. Aisner, L. Sholl, B. E. Johnson, D. J. Kwiatkowski, I. I. Wistuba, P. A. Bunn, Jr., J. Minna, G. Xiao, M. G. Kris, Y. Xie, J. Clin. Invest. 2023, 133, e160330.

[83] J. M. Chang, A. E. McCullough, A. C. Dueck, H. E. Kosiorek, I. T. Ocal, T. K. Lidner, R. J. Gray, N. Wasif, D. W. Northfelt, K. S. Anderson, Ann. Surg Oncol. 2015, 22, 509.

[84] S. Azarianpour, G. Corredor, K. Bera, P. Leo, P. Fu, P. Toro, A. Joehlin-Price, M. Mokhtari, H. Mahdi, A. Madabhushi, J. Immunother. Cancer 2022, 10, e003833.

[85] J. Xie, X. Pu, J. He, Y. Qiu, C. Lu, W. Gao, X. Wang, H. Lu, J. Shi, Y. Xu, A. Madabhushi, X. Fan, J. Chen, J. Xu, Comput. Biol. Med. 2022, 146, 105520.

[86] S. Ali, R. Veltri, J. A. Epstein, C. Christudass, A. Madabhushi, in Proceeding of Medical Imaging 2013: Digital Pathology, Lake Buena Vista (Orlando Area), Florida, USA 2013, pp. 164–174.

[87] G. Lee, R. Sparks, S. Ali, N. N. Shih, M. D. Feldman, E. Spangler, T. Rebbeck, J. E. Tomaszewski, A. Madabhushi, PLoS One 2014, 9, e97954.

[88] A. Saito, Y. Numata, T. Hamada, T. Horisawa, E. Cosatto, H. P. Graf, M. Kuroda, Y. Yamamoto, J. Pathol. Inform 2016, 7, 36.

[89] C. Lu, J. S. Lewis, Jr., W. D. Dupont, W. D. Plummer, Jr., A. Janowczyk, A. Madabhushi, Mod. Pathol. 2017, 30, 1655.

[90] J. Cheng, Y. Liu, W. Huang, W. Hong, L. Wang, X. Zhan, Z. Han, D. Ni, K. Huang, J. Zhang, Front. Oncol. 2021, 11, 623382.

[91] T. Wu, S. He, J. Liu, S. Sun, K. Liu, Q.-L. Han, Y. Tang, IEEE/CAA J. Automatica Sinica 2023, 10, 1122.

[92] R. R. Selvaraju, M. Cogswell, A. Das, R. Vedantam, D. Parikh, D. Batra, in Proceedings of the IEEE International Conference on Computer Vision (ICCV) 2017, pp. 618–626.

[93] A. Chattopadhay, A. Sarkar, P. Howlader, V. N. Balasubramanian, in 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, Lake Tahoe, NV, USA 2018, pp. 839–847.

[94] Z. Ying, D. Bourgeois, J. You, M. Zitnik, J. Leskovec, in Proceedings of the 33rd International Conference on Neural Information Processing Systems, Vancouver Convention Center, Vancouver, Canada 2019, pp. 9244–9255.

[95] H. Naji, J. I. Pisula, S. Ugliano, A. Simon, R. Buettner, K. Bozek, (Preprint) bioRxiv 2024.

[96] A. S. Kornilov, I. V. Safonov, J. Imaging 2018, 4, 123.

[97] O. Ronneberger, P. Fischer, T. Brox, in Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015, Vol. 9351 (Eds: N. Navab, J. Hornegger, W. Wells, A. Frangi), Springer, Cham 2015, pp. 234–241.

[98] S. Graham, Q. D. Vu, S. E. A. Raza, A. Azam, Y. W. Tsang, J. T. Kwak, N. Rajpoot, Med. Image Anal. 2019, 58, 101563.

[99] Y. Zhou, O. F. Onder, Q. Dou, E. Tsougenis, H. Chen, P.-A. Heng, in Information Processing in Medical Imaging, Vol. 11492 (Eds: A. Chung, J. Gee, P. Yushkevich, S. Bao), Springer, Cham 2019, pp. 682–693.

[100] S. Graham, H. Chen, J. Gamper, Q. Dou, P.-A. Heng, D. Snead, Y. W. Tsang, N. Rajpoot, Med. Image Anal. 2019, 52, 199.

[101] M. M. Fraz, S. A. Khurram, S. Graham, M. Shaban, M. Hassan, A. Loya, N. M. Rajpoot, Neural Comput. 2020, 32, 9915.

[102] R. Deng, Q. Liu, C. Cui, Z. Asad, H. Yang, Y. Huo, (Preprint) arXiv, 2112.12665v2, v2, 2022.

[103] C. P. Jayapandian, Y. Chen, A. R. Janowczyk, M. B. Palmer, C. A. Cassol, M. Sekulic, J. B. Hodgin, J. Zee, S. M. Hewitt, J. O’Toole, Kidney Int. 2021, 99, 86.

[104] R. Deng, Q. Liu, C. Cui, T. Yao, J. Long, Z. Asad, R. M. Womick, Z. Zhu, A. B. Fogo, S. Zhao, in IEEE Transactions on Biomedical Engineering, Vol. 70, IEEE, 2023, pp. 2636–2644.

[105] A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo, in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 4015–4026.

[106] Y. Zhang, T. Zhou, S. Wang, P. Liang, Y. Zhang, D. Z. Chen, in Medical Image Computing and Computer Assisted Intervention–MICCAI 2023 Workshops, Vol. 14393 (Eds: M. E. Celebi, M. S. Salekin, H. Kim, S. Albarqouni, C. Barata, A. Halpern, P. Tschandl, M. Combalia, Y. Liu, G. Zamzmi, J. Levy, H. Rangwala, A. Reinke, D. Wynn, B. Landman, W.-K. Jeong, Y. Shen, Z. Deng, S. Bakas, X. Li, C. Qin, N. Rieke, H. Roth, D. Xu), Springer, Cham 2023, pp. 129–139.

[107] R. S. Vanguri, J. Luo, A. T. Aukerman, J. V. Egger, C. J. Fong, N. Horvat, A. Pagano, J. d. A. B. Araujo-Filho, L. Geneslaw, H. Rizvi, R. Sosa, K. M. Boehm, S.-R. Yang, F. M. Bodd, K. Ventura, T. J. Hollmann, M. S. Ginsberg, J. Gao, MSK MIND Consortium, M. D. Hellmann, J. L. Sauter, S. P. Shah, Nat. Cancer 2022, 3, 1151.

RIGHTS & PERMISSIONS

2024 The Author(s). Interdisciplinary Medicine published by Wiley-VCH GmbH on behalf of Nanfang Hospital, Southern Medical University.