J. van der Laak

Latest

• Deep learning in histopathology: the path to the clinic.
• Residual cyclegan for robust domain transformation of histopathological tissue slides.
• Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics.
• Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels.
• Neural Image Compression for Gigapixel Histopathology Image Analysis.
• Tailoring automated data augmentation to H&E-stained histopathology
• Impact of rescanning and normalization on convolutional neural network performance in multi-center, whole-slide classification of prostate cancer
• Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study
• Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks
• No pixel-level annotations needed
• Learning to detect lymphocytes in immunohistochemistry with deep learning
• Neural Image Compression for Gigapixel Histopathology Image Analysis
• Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology.
• Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer
• Resolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networks
• From detection of individual metastases to classification of lymph node status at the patient level: the CAMELYON17 challenge
• 1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset
• Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks
• Automated segmentation of epithelial tissue in prostatectomy slides using deep learning
• Automatic color unmixing of IHC stained whole slide images
• H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection
• Convolutional Neural Networks for Lymphocyte detection in Immunohistochemically Stained Whole-Slide Images
• Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
• Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images
• Evaluation of tongue squamous cell carcinoma resection margins using ex-vivo MR.
• The importance of stain normalization in colorectal tissue classification with convolutional networks
• A Survey on Deep Learning in Medical Image Analysis
• Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images
• Stain specific standardization of whole-slide histopathological images
• Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
• A multi-scale superpixel classification approach for region of interest detection in whole slide histopathology images
• Automated detection of prostate cancer in digitized whole-slide images of H&E-stained biopsy specimens