An Open Source Platform for Computational Histopathology
暂无分享,去创建一个
Xiaxia Yu | Hongping Song | Bingshuai Zhao | Haofan Huang | Mu Tian | Sai Zhang | Zengshan Li | Kun Huang | Yi Gao | Xiaxia Yu | Yi Gao | Kun Huang | Zeng-shan Li | Haofan Huang | Mu Tian | Hongping Song | Sai Zhang | Bingshuai Zhao
[1] Eric Cosatto,et al. Classification of mitotic figures with convolutional neural networks and seeded blob features , 2013, Journal of pathology informatics.
[2] Joel H. Saltz,et al. caGrid: design and implementation of the core architecture of the cancer biomedical informatics grid , 2006, Bioinform..
[3] Nasir M. Rajpoot,et al. A Stochastic Polygons Model for Glandular Structures in Colon Histology Images , 2015, IEEE Transactions on Medical Imaging.
[4] Mohammad Sohel Rahman,et al. MultiResUNet : Rethinking the U-Net Architecture for Multimodal Biomedical Image Segmentation , 2019, Neural Networks.
[5] Joel H. Saltz,et al. Machine-Based Morphologic Analysis of Glioblastoma Using Whole-Slide Pathology Images Uncovers Clinically Relevant Molecular Correlates , 2013, PloS one.
[6] A. Ruifrok,et al. Quantification of histochemical staining by color deconvolution. , 2001, Analytical and quantitative cytology and histology.
[7] Jakub Nalepa,et al. Multi-scale Voting Classifiers for Breast-Cancer Histology Images , 2018, INCoS.
[8] Ron Kikinis,et al. 3D Slicer , 2012, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).
[9] Peter Bankhead,et al. QuPath: Open source software for digital pathology image analysis , 2017, Scientific Reports.
[10] Yi Gao,et al. A Containerized Software System for Generation, Management, and Exploration of Features from Whole Slide Tissue Images. , 2017, Cancer research.
[11] Max A. Viergever,et al. Breast Cancer Histopathology Image Analysis: A Review , 2014, IEEE Transactions on Biomedical Engineering.
[12] Tony F. Chan,et al. Active contours without edges , 2001, IEEE Trans. Image Process..
[13] Gyan Bhanot,et al. Computerized Image-Based Detection and Grading of Lymphocytic Infiltration in HER2+ Breast Cancer Histopathology , 2010, IEEE Transactions on Biomedical Engineering.
[14] Yizong Cheng,et al. Mean Shift, Mode Seeking, and Clustering , 1995, IEEE Trans. Pattern Anal. Mach. Intell..
[15] Rajarsi R. Gupta,et al. Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images. , 2018, Cell reports.
[16] Joel H. Saltz,et al. Hierarchical nucleus segmentation in digital pathology images , 2016, SPIE Medical Imaging.
[17] Milan Sonka,et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.
[18] Hui Kong,et al. Partitioning Histopathological Images: An Integrated Framework for Supervised Color-Texture Segmentation and Cell Splitting , 2011, IEEE Transactions on Medical Imaging.
[19] A. Madabhushi,et al. Histopathological Image Analysis: A Review , 2009, IEEE Reviews in Biomedical Engineering.
[20] H. Irshad,et al. Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review—Current Status and Future Potential , 2014, IEEE Reviews in Biomedical Engineering.
[21] Hai Su,et al. High-throughput histopathological image analysis via robust cell segmentation and hashing , 2015, Medical Image Anal..
[22] Guido Gerig,et al. User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.
[23] Anant Madabhushi,et al. Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[24] Dorin Comaniciu,et al. Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[25] Vijayan K. Asari,et al. Nuclei Segmentation with Recurrent Residual Convolutional Neural Networks based U-Net (R2U-Net) , 2018, NAECON 2018 - IEEE National Aerospace and Electronics Conference.
[26] Pierre Alliez,et al. Can semantic labeling methods generalize to any city? the inria aerial image labeling benchmark , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[27] Dimitris N. Metaxas,et al. Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images , 2020, IEEE Transactions on Medical Imaging.
[28] Anthony J. Yezzi,et al. A statistical approach to snakes for bimodal and trimodal imagery , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[29] Ron Kikinis,et al. An Effective Interactive Medical Image Segmentation Method Using Fast GrowCut , 2014 .
[30] Guido Gerig,et al. ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[31] Kevin W Eliceiri,et al. NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.
[32] A. Huisman,et al. Automatic Nuclei Segmentation in H&E Stained Breast Cancer Histopathology Images , 2013, PloS one.
[33] Lin Yang,et al. Robust Segmentation of Overlapping Cells in Histopathology Specimens Using Parallel Seed Detection and Repulsive Level Set , 2012, IEEE Transactions on Biomedical Engineering.
[34] Yukako Yagi,et al. Color standardization and optimization in Whole Slide Imaging , 2011, Diagnostic pathology.
[35] Shidan Wang,et al. Pathology Image Analysis Using Segmentation Deep Learning Algorithms. , 2019, The American journal of pathology.
[36] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[37] Andriy Fedorov,et al. Computational Radiomics System to Decode the Radiographic Phenotype. , 2017, Cancer research.
[38] Peter Meer,et al. Unsupervised segmentation based on robust estimation and color active contour models , 2005, IEEE Transactions on Information Technology in Biomedicine.
[39] Juho Kannala,et al. Mask-RCNN and U-Net Ensembled for Nuclei Segmentation , 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).
[40] J. S. Marron,et al. A method for normalizing histology slides for quantitative analysis , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[41] Mitko Veta,et al. Detecting mitotic figures in breast cancer histopathology images , 2013, Medical Imaging.
[42] Joel H. Saltz,et al. The Proneural Molecular Signature Is Enriched in Oligodendrogliomas and Predicts Improved Survival among Diffuse Gliomas , 2010, PloS one.
[43] Yao Lu,et al. RIC-Unet: An Improved Neural Network Based on Unet for Nuclei Segmentation in Histology Images , 2019, IEEE Access.
[44] Thomas J. Fuchs,et al. Clinical-grade computational pathology using weakly supervised deep learning on whole slide images , 2019, Nature Medicine.
[45] Mahadev Satyanarayanan,et al. OpenSlide: A vendor-neutral software foundation for digital pathology , 2013, Journal of pathology informatics.
[46] Ron Kikinis,et al. Large scale digital prostate pathology image analysis combining feature extraction and deep neural network , 2017, ArXiv.
[47] Mbbs Md FRCPath Donald N. Pritzker Vinay Kumar. Robbins and Cotran pathologic basis of disease , 2015 .
[48] Hao Chen,et al. Gland segmentation in colon histology images: The glas challenge contest , 2016, Medical Image Anal..
[49] Lin Yang,et al. An Automatic Learning-Based Framework for Robust Nucleus Segmentation , 2016, IEEE Transactions on Medical Imaging.
[50] Jiang Gu,et al. Virtual microscopy and virtual slides in teaching, diagnosis, and research , 2005 .
[51] Hao Chen,et al. A Multi-Organ Nucleus Segmentation Challenge , 2020, IEEE Transactions on Medical Imaging.
[52] Surabhi Bhargava,et al. A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology , 2017, IEEE Transactions on Medical Imaging.