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Self-Supervised Learning for Volumetric Imaging: A Prostate Cancer Biparametric Magnetic Resonance Imaging Case Study

https://doi.org/10.2139/ssrn.4864797
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/mp.13367openalex-extracted
Prostate cancer classification with multiparametric MRI transfer learning model
inferredcites →https://doi.org/10.1007/978-0-387-84858-7_2openalex-extracted
Overview of Supervised Learning
inferredcites →https://doi.org/10.1007/978-3-030-11024-6_37openalex-extracted
Pre-training on Grayscale ImageNet Improves Medical Image Classification
inferredcites →https://doi.org/10.1007/978-3-031-13324-4_27openalex-extracted
On the Effectiveness of 3D Vision Transformers for the Prediction of Prostate Cancer Aggressiveness
inferredcites →https://doi.org/10.1007/s00261-018-1824-5openalex-extracted
Deep transfer learning-based prostate cancer classification using 3 Tesla multi-parametric MRI
inferredcites →https://doi.org/10.1007/s00330-020-06912-8openalex-extracted
Survival-relevant high-risk subregion identification for glioblastoma patients: the MRI-based multiple instance learning approach
inferredcites →https://doi.org/10.1007/s13246-020-00865-4openalex-extracted
Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks
inferredcites →https://doi.org/10.1016/j.crad.2015.06.093openalex-extracted
PI-RADS version 2: what you need to know
inferredcites →https://doi.org/10.1016/j.media.2014.04.006openalex-extracted
Multiple instance learning for classification of dementia in brain MRI
inferredcites →https://doi.org/10.1016/j.xcrm.2023.100980openalex-extracted
Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study
inferredcites →https://doi.org/10.1038/s41551-022-00914-1openalex-extracted
Self-supervised learning in medicine and healthcare
inferredcites →https://doi.org/10.1038/s41551-022-00929-8openalex-extracted
Fast and scalable search of whole-slide images via self-supervised deep learning
inferredcites →https://doi.org/10.1038/s41598-023-33339-0openalex-extracted
Value of handcrafted and deep radiomic features towards training robust machine learning classifiers for prediction of prostate cancer disease aggressiveness
inferredcites →https://doi.org/10.1038/s41698-023-00365-0openalex-extracted
Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology
inferredcites →https://doi.org/10.1038/s41746-023-00811-0openalex-extracted
Self-supervised learning for medical image classification: a systematic review and implementation guidelines
inferredcites →https://doi.org/10.1097/pas.0000000000000530openalex-extracted
The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma
inferredcites →https://doi.org/10.1109/access.2021.3125324openalex-extracted
Self-Supervised Deep Convolutional Neural Network for Chest X-Ray Classification
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-extracted
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01167openalex-extracted
A ConvNet for the 2020s
inferredcites →https://doi.org/10.1109/cvpr52729.2023.01499openalex-extracted
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
inferredcites →https://doi.org/10.1109/iccv48922.2021.00391openalex-extracted
GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition
inferredcites →https://doi.org/10.1109/isbi52829.2022.9761573openalex-extracted
Contrasting Axial T2W MRI for Prostate Cancer Triage: A Self-Supervised Learning Approach
inferredcites →https://doi.org/10.1109/tbme.2020.2993528openalex-extracted
Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI
inferredcites →https://doi.org/10.1117/12.2581557openalex-extracted
Clinically significant prostate cancer detection on MRI with self-supervised learning using image context restoration
inferredcites →https://doi.org/10.1148/radiol.2020192224openalex-extracted
Preparing Medical Imaging Data for Machine Learning
inferredcites →https://doi.org/10.1148/ryai.230031openalex-extracted
Semisupervised Learning with Report-guided Pseudo Labels for Deep Learning–based Prostate Cancer Detection Using Biparametric MRI
inferredcites →https://doi.org/10.3390/cancers12061606openalex-extracted
Automated Classification of Significant Prostate Cancer on MRI: A Systematic Review on the Performance of Machine Learning Applications
inferredcites →https://doi.org/10.3390/diagnostics12020289openalex-extracted
Machine Learning in Prostate MRI for Prostate Cancer: Current Status and Future Opportunities
inferredcites →https://doi.org/10.3390/diagnostics13223488openalex-extracted
Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate—Unnecessary or Underutilised? A Narrative Review
inferredcites →https://doi.org/10.4102/sajr.v25i1.2062openalex-extracted
PI-RADS v2.1: What has changed and how to report
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-extracted
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-extracted
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
inferredcites →https://doi.org/10.48550/arxiv.1505.00853openalex-extracted
Empirical Evaluation of Rectified Activations in Convolutional Network
inferredcites →https://doi.org/10.48550/arxiv.1912.01703openalex-extracted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
inferredcites →https://doi.org/10.48550/arxiv.2010.11929openalex-extracted
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
inferredcites →https://doi.org/10.48550/arxiv.2206.02574openalex-extracted
On the duality between contrastive and non-contrastive self-supervised learning
inferredcites →https://doi.org/10.48550/arxiv.2304.12210openalex-extracted
inferredcites →https://doi.org/10.56530/lcgc.eu.dk3677x5openalex-extracted
What Are Orphan Data?
inferredcites →https://doi.org/10.1016/j.media.2020.101794openalex-snapshot
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01553openalex-snapshot
Masked Autoencoders Are Scalable Vision Learners
inferredcites →https://doi.org/10.13016/m2wqeu-njzeopenalex-snapshot
A Cookbook of Self-Supervised Learning

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1186/s13244-025-02056-9openalex-snapshot
Foundation models for radiology—the position of the AI for Health Imaging (AI4HI) network
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