| Streaming Convolutional Neural Networks for End-to-End Learning With Multi-Megapixel Images | 0 | 0.34 | 2022 |
| Tailoring automated data augmentation to H&E-stained histopathology. | 0 | 0.34 | 2021 |
| Residual cyclegan for robust domain transformation of histopathological tissue slides | 2 | 0.44 | 2021 |
| Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels | 0 | 0.34 | 2021 |
| Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images—The ACDC@LungHP Challenge 2019 | 1 | 0.35 | 2021 |
| Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks. | 0 | 0.34 | 2020 |
| High resolution whole prostate biopsy classification using streaming stochastic gradient descent. | 0 | 0.34 | 2019 |
| Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification. | 0 | 0.34 | 2019 |
| Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology. | 9 | 0.93 | 2019 |
| A large annotated medical image dataset for the development and evaluation of segmentation algorithms. | 9 | 0.48 | 2019 |
| From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge. | 8 | 0.47 | 2019 |
| Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology. | 0 | 0.34 | 2019 |
| Learning to detect lymphocytes in immunohistochemistry with deep learning. | 4 | 0.38 | 2019 |
| Automated segmentation of epithelial tissue in prostatectomy slides using deep learning. | 0 | 0.34 | 2018 |
| Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study. | 0 | 0.34 | 2018 |
| Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders. | 0 | 0.34 | 2018 |
| H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection. | 0 | 0.34 | 2018 |
| Automatic color unmixing of IHC stained whole slide images. | 0 | 0.34 | 2018 |
| Epithelium Segmentation Using Deep Learning In H&E-Stained Prostate Specimens With Immunohistochemistry As Reference Standard | 2 | 0.42 | 2018 |
| Automatic segmentation of histopathological slides of renal tissue using deep learning. | 1 | 0.37 | 2018 |
| Training convolutional neural networks with megapixel images. | 0 | 0.34 | 2018 |
| Neural Image Compression for Gigapixel Histopathology Image Analysis | 4 | 0.54 | 2018 |
| Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks. | 8 | 0.56 | 2018 |
| The importance of stain normalization in colorectal tissue classification with convolutional networks | 13 | 0.65 | 2017 |
| Large scale deep learning for computer aided detection of mammographic lesions. | 71 | 2.40 | 2017 |
| Evaluation of tongue squamous cell carcinoma resection margins using ex-vivo MR. | 0 | 0.34 | 2017 |
| A Survey on Deep Learning in Medical Image Analysis. | 617 | 21.68 | 2017 |
| Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images. | 6 | 0.61 | 2017 |
| Location Sensitive Deep Convolutional Neural Networks For Segmentation Of White Matter Hyperintensities | 22 | 0.86 | 2016 |
| Stain Specific Standardization of Whole-Slide Histopathological Images. | 27 | 1.32 | 2016 |
| Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks | 46 | 1.48 | 2016 |
| Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images. | 13 | 0.78 | 2016 |
| Automated robust registration of grossly misregistered whole-slide images with varying stains. | 0 | 0.34 | 2016 |
| A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images | 4 | 0.43 | 2015 |
| Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens | 0 | 0.34 | 2015 |
| Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI | 2 | 0.41 | 2014 |
| Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge. | 55 | 2.73 | 2014 |
| Distinguishing benign confounding treatment changes from residual prostate cancer on MRI following laser ablation | 0 | 0.34 | 2014 |
| Computer-Aided Detection of Prostate Cancer in MRI | 45 | 2.62 | 2014 |
| Automated computer-aided detection of prostate cancer in MR images: from a whole-organ to a zone-based approach | 5 | 0.94 | 2012 |
| A pattern recognition approach to zonal segmentation of the prostate on MRI. | 9 | 1.01 | 2012 |
| Required accuracy of MR-US registration for prostate biopsies | 4 | 0.54 | 2011 |
| Automatic computer aided detection of abnormalities in multi-parametric prostate MRI | 9 | 0.96 | 2011 |
| Computer aided detection of prostate cancer using T2, DWI and DCE MRI: methods and clinical applications | 0 | 0.34 | 2010 |
| Simulation of nodules and diffuse infiltrates in chest radiographs using CT templates | 0 | 0.34 | 2010 |
