Topology Aware Fully Convolutional Networks for Histology Gland Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404

Fully convolutional networks for semantic segmentation

Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834

Caffe: Convolutional Architecture for Fast Feature Embedding

Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., & Darrell, T. (2014) · Proceedings of the 22nd ACM international conference on Multimedia · doi:10.1145/2647868.2654889 · Cited by 11,077

pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long‐term follow‐up

Elston, C. W., & Ellis, I. O. (1991) · Histopathology · doi:10.1111/j.1365-2559.1991.tb00229.x · Cited by 6,181

Learning Deconvolution Network for Semantic Segmentation

Noh, H., Hong, S., & Han, B. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.178 · Cited by 4,422

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2014) · arXiv · doi:10.48550/arxiv.1412.7062 · Cited by 4,213

Conditional Random Fields as Recurrent Neural Networks

Zheng, S., Jayasumana, S., Romera-Paredes, B., Vineet, V., Su, Z., Du, D., Huang, C., & Torr, P. H. S. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.179 · Cited by 2,386

Gleason grading and prognostic factors in carcinoma of the prostate

Humphrey, P. A. (2004) · Modern Pathology · doi:10.1038/modpathol.3800054 · Cited by 525

Large-Scale Object Classification Using Label Relation Graphs

Deng, J., Ding, N., Jia, Y., Frome, A., Murphy, K. P., Samy Bengio, A., Li, Y., Neven, H., & Adam, H. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10590-1_4 · Cited by 371

A Stochastic Polygons Model for Glandular Structures in Colon Histology Images

Sirinukunwattana, K., Snead, D. R. J., & Rajpoot, N. (2015) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2015.2433900 · Cited by 257

Automatic segmentation of colon glands using object-graphs

Gündüz-Demir, Ç., Kandemir, M., Tosun, A. B., & Sökmensüer, C. (2009) · Medical Image Analysis · doi:10.1016/j.media.2009.09.001 · Cited by 146

Globally optimal segmentation of multi-region objects

Delong, A., & Boykov, Y. Y. (2009) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459263 · Cited by 126

Local Optimization Based Segmentation of Spatially-Recurring, Multi-Region Objects With Part Configuration Constraints

Nosrati, M. S., & Hamarneh, G. (2014) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2014.2323074 · Cited by 16

Gland Segmentation in Colon Histology Images: The GlaS Challenge ContestPreprint

Sirinukunwattana, K., Pluim, J. P. W., Chen, H., Qi, X., Heng, P., Guo, Y. B., Wang, L. Y., Matuszewski, B. J., Bruni, E., Sanchez, U., et al. (2016) · Zurich Open Repository and Archive (University of Zurich) · doi:10.3929/ethz-b-000127185 · Cited by 10

Bounded Labeling Function for Global Segmentation of Multi-part Objects with Geometric Constraints

Nosrati, M. S., Andrews, S., & Hamarneh, G. (2013) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.254 · Cited by 8

A survey on deep learning in medical image analysis

Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.07.005 · Cited by 15,332

Deep learning-enabled medical computer vision

Esteva, A., Chou, K., Yeung, S., Naik, N., Madani, A., Mottaghi, A., Liu, Y., Topol, E., Dean, J., & Socher, R. (2021) · npj Digital Medicine · doi:10.1038/s41746-020-00376-2 · Cited by 1,406

Deep semantic segmentation of natural and medical images: a review

Taghanaki, S. A., Abhishek, K., Cohen, J., Cohen‐Adad, J., & Hamarneh, G. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-020-09854-1 · Cited by 929

Anatomically constrained neural networks (ACNNS): application to cardiac image enhancement and segmentation

Oktay, O., Ferrante, E., Kamnitsas, K., Heinrich, M., Bai, W., Caballero, J., Cook, S. A., de Marvao, A., Dawes, T., O'Regan, D. P., et al. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2017.2743464 · Cited by 751

Deep neural network models for computational histopathology: A survey

Srinidhi, C. L., Ciga, O., & Martel, A. L. (2021) · Medical Image Analysis · doi:10.1016/j.media.2020.101813 · Cited by 749

TA-Net: Topology-Aware Network for Gland Segmentation

Wang, H., Xian, M., & Vakanski, A. (2022) · IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) · doi:10.1109/wacv51458.2022.00330 · Cited by 28

Introducing soft topology constraints in deep learning-based segmentation using projected pooling loss

Fu, G., Jurdi, R. E., Chougar, L., Dormont, D., Valabrègue, R., Lehéricy, S., & Colliot, O. (2023) · SPIE Medical Imaging: Image Processing · doi:10.1117/12.2651576 · Cited by 3

Deep learning meets topology-preserving active contours: towards scalable quantitative histology of cortical cytoarchitecture.Preprint

Thierbach, K., Bazin, P., Gavriilidis, F., Kirilina, E. P., Jager, C., Morawski, M., Geyer, S., Weiskopf, N., & Scherf, N. (2019) · Data Archiving and Networked Services (DANS) · Cited by 2

A Topological Loss Function for Deep-Learning Based Image Segmentation Using Persistent Homology

Clough, J. R., Byrne, N., Öksüz, İ., Zimmer, V. A., Schnabel, J. A., & King, A. P. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3013679 · Cited by 281

Topology-Aware Segmentation Using Discrete Morse Theory

Hu, X., Wang, Y., Li, F., Samaras, D., & Chen, C. (2021) · PubMed · doi:10.48550/arxiv.2103.09992 · Cited by 38