Research graph
References from Using multi-label ensemble CNN classifiers to mitigate labelling inconsistencies in patch-level Gleason grading. Local targets link to admitted publications; unresolved targets remain external evidence.
Deep learning in digital pathology image analysis: a survey
10.1007/s11684-020-0782-9 · 2020 · External reference
10.1109/cvprw.2018.00303
10.1109/cvprw.2018.00303 · External reference
Clinical applications of graph neural networks in computational histopathology: A review
10.1016/j.compbiomed.2023.107201 · 2023 · External reference
Machine learning in computational histopathology: Challenges and opportunities
10.1002/gcc.23177 · 2023 · External reference
Artificial intelligence in prostate cancer: Definitions, current research, and future directions
10.1016/j.urolonc.2022.03.003 · 2022 · External reference
Computational Pathology: A Survey Review and The Way Forward
10.1016/j.jpi.2023.100357 · 2024 · External reference
Deep Learning Methodologies Applied to Digital Pathology in Prostate Cancer: A Systematic Review
10.3390/diagnostics13162676 · 2023 · External reference
Paradigm shift from Artificial Neural Networks (ANNs) to deep Convolutional Neural Networks (DCNNs) in the field of medical image processing
10.1016/j.eswa.2023.122983 · 2024 · External reference
Bibliometric analysis of the global scientific production on machine learning applied to different cancer types
10.1007/s11356-023-28576-9 · 2023 · External reference
A systematic review and meta-analysis of artificial intelligence diagnostic accuracy in prostate cancer histology identification and grading
10.1038/s41391-023-00673-3 · 2023 · External reference
Application of support vector machine algorithm for early differential diagnosis of prostate cancer
10.1016/j.dsm.2022.10.001 · 2023 · External reference
Prostate Cancer, Version 1.2016
10.6004/jnccn.2016.0004 · 2016 · External reference
Deep Learning in Prostate Cancer Diagnosis Using Multiparametric Magnetic Resonance Imaging With Whole-Mount Histopathology Referenced Delineations
2022 · External reference
10.1007/978-3-030-71975-3_14
10.1007/978-3-030-71975-3_14 · 2021 · External reference
The Devil is in the Details: Whole Slide Image Acquisition and Processing for Artifacts Detection, Color Variation, and Data Augmentation: A Review
10.1109/access.2022.3176091 · 2022 · External reference
10.1109/sipaim56729.2023.10373416
10.1109/sipaim56729.2023.10373416 · External reference
Prostate cancer grade using self-supervised learning and novel feature aggregator based on weakly-labeled gbit-pixel pathology images
10.1007/s10489-023-05224-w · 2024 · External reference
Toward More Transparent and Accurate Cancer Diagnosis With an Unsupervised CAE Approach
10.1109/access.2023.3343845 · 2023 · External reference
10.23919/eusipco58844.2023.10289741
10.23919/eusipco58844.2023.10289741 · External reference
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images
10.1016/j.patcog.2023.110057 · 2024 · External reference
Deep Learning-Based Gleason Grading of Prostate Cancer From Histopathology Images—Role of Multiscale Decision Aggregation and Data Augmentation
10.1109/jbhi.2019.2944643 · 2020 · External reference
Image-based patch selection for deep learning to improve automated Gleason grading in histopathological slides
2020 · External reference
Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies
10.1007/s00428-019-02577-x · 2019 · External reference
Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance Learning
10.1109/access.2022.3143345 · 2022 · External reference
Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
10.1038/s41591-021-01620-2 · 2022 · External reference
Weakly supervised joint whole-slide segmentation and classification in prostate cancer
10.1016/j.media.2023.102915 · 2023 · External reference
ProGleason-GAN: Conditional progressive growing GAN for prostatic cancer Gleason grade patch synthesis
10.1016/j.cmpb.2023.107695 · 2023 · External reference
10.23919/eusipco58844.2023.10289846
10.23919/eusipco58844.2023.10289846 · External reference
Going Deeper through the Gleason Scoring Scale: An Automatic end-to-end System for Histology Prostate Grading and Cribriform Pattern Detection
10.1016/j.cmpb.2020.105637 · 2020 · External reference
Automated detection of cribriform growth patterns in prostate histology images
10.1038/s41598-020-71942-7 · 2020 · External reference
Unresolved reference
2021 · External reference
Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis
10.1016/j.media.2020.101759 · 2020 · External reference
A loss-based patch label denoising method for improving whole-slide image analysis using a convolutional neural network
10.1038/s41598-022-05001-8 · 2022 · External reference
Unresolved reference
2024 · External reference
ImageNet Large Scale Visual Recognition Challenge
10.1007/s11263-015-0816-y · 2015 · External reference
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
10.1007/s11263-019-01228-7 · 2020 · External reference
