Machine learning model for fast prediction and uncertainty quantification of needle deflection during prostate biopsy
Fuente:
Wiley Open Access
Saved in:
| Main Authors: | Nathan Hoffman, Lidia Al‐Zogbi, Axel Krieger, Junichi Tokuda, Pedro Moreira, Mark Fuge |
|---|---|
| Format: | Artículo Open Access |
| Published: |
Wiley
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Impact of deep learning model uncertainty on manual corrections to auto-segmentation in prostate cancer radiotherapy
by: Rogowski, Viktor, et al.
Published: (2025)
by: Rogowski, Viktor, et al.
Published: (2025)
Rapid CNN‐based needle localization for automatic slice alignment in MR‐guided interventions using 3D undersampled radial white‐marker imaging
by: Jonas Frederik Faust, et al.
Published: (2024)
by: Jonas Frederik Faust, et al.
Published: (2024)
Radiological mapping and uncertainty quantification by a fast Microcanonical Langevin Monte Carlo sampler
by: Pan, Lei, et al.
Published: (2026)
by: Pan, Lei, et al.
Published: (2026)
Deep learning‐based dose prediction for magnetic resonance‐guided prostate radiotherapy
by: Samuel Fransson, et al.
Published: (2024)
by: Samuel Fransson, et al.
Published: (2024)
A novel method for pharmacokinetic parameters quantification in DCE‐MRI: Application in prostate cancer
by: Jhonalbert Aponte, et al.
Published: (2026)
by: Jhonalbert Aponte, et al.
Published: (2026)
A tandem reinforcement learning framework for localized prostate cancer treatment planning and machine parameter optimization
by: Nathan Shaffer, et al.
Published: (2026)
by: Nathan Shaffer, et al.
Published: (2026)
A new method of modeling the multi-stage decision-making process of CRT using machine learning with uncertainty quantification
by: Larsen, Kristoffer, et al.
Published: (2023)
by: Larsen, Kristoffer, et al.
Published: (2023)
A systematic evaluation of uncertainty quantification techniques in deep learning: a case study in photoplethysmography signal analysis
by: Bench, Ciaran, et al.
Published: (2025)
by: Bench, Ciaran, et al.
Published: (2025)
Shape Manipulation of Bevel-Tip Needles for Prostate Biopsy Procedures: A Comparison of Two Resolved-Rate Controllers
by: Wang, Yanzhou, et al.
Published: (2024)
by: Wang, Yanzhou, et al.
Published: (2024)
Uncertainty quantification for improving radiomic-based models in radiation pneumonitis prediction
by: Puttanawarut, Chanon, et al.
Published: (2024)
by: Puttanawarut, Chanon, et al.
Published: (2024)
Assessing Hemodynamic Impact of Tissue-Engineered Vascular Graft Displacement: Combining Postoperative in vivo Results and Computational Modeling to Improve Surgical Planning
by: Aslan, Seda, et al.
Published: (2026)
by: Aslan, Seda, et al.
Published: (2026)
Automated HER2 scoring with uncertainty quantification using lensfree holography and deep learning
by: Shen, Che-Yung, et al.
Published: (2026)
by: Shen, Che-Yung, et al.
Published: (2026)
Dexterous Intramyocardial Needle Ablation (d-INA): Design, Fabrication, and In-Vivo Validation
by: Zhou, Chang, et al.
Published: (2025)
by: Zhou, Chang, et al.
Published: (2025)
The costs and benefits of a prison needle and syringe program in Australia, 2025–30: a modelling study
by: Farah Houdroge, et al.
Published: (2025)
by: Farah Houdroge, et al.
Published: (2025)
A deep‐learning framework for the prediction of the type of adaptive strategy of MR‐guided prostate radiotherapy
by: Wenlong Xia, et al.
Published: (2025)
by: Wenlong Xia, et al.
Published: (2025)
Single‐ versus multi‐model in the deep learning prediction of monitor units per control point for automated treatment planning in prostate cancer
by: Mathieu Gaudreault, et al.
Published: (2025)
by: Mathieu Gaudreault, et al.
Published: (2025)
Can input reconstruction be used to directly estimate uncertainty of a dose prediction U‐Net model?
by: Margerie Huet‐Dastarac, et al.
Published: (2024)
by: Margerie Huet‐Dastarac, et al.
Published: (2024)
Enhancing accuracy in proton therapy: The impact of geometric uncertainty models in head and neck cancer treatment
by: Ying Zhang, et al.
Published: (2025)
by: Ying Zhang, et al.
Published: (2025)
Uncertainty quantification in neural network-based glucose prediction for diabetes
by: Tan, Hai Siong, et al.
Published: (2026)
by: Tan, Hai Siong, et al.
Published: (2026)
All-optical photoacoustic tomography via beam deflection
by: Yan, Xingchi, et al.
Published: (2026)
by: Yan, Xingchi, et al.
Published: (2026)
Superparamagnetic iron oxide nanoparticle enhanced percutaneous microwave ablation: Ex‐vivo characterization using magnetic resonance thermometry
by: Sharath K. Bhagavatula, et al.
Published: (2024)
by: Sharath K. Bhagavatula, et al.
Published: (2024)
Novel pre‐spatial data fusion deep learning approach for multimodal volumetric outcome prediction models in radiotherapy
by: John C. Asbach, et al.
Published: (2025)
by: John C. Asbach, et al.
Published: (2025)
Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer
by: Amin Talebi, et al.
Published: (2024)
by: Amin Talebi, et al.
Published: (2024)
PSMA PET/MRI‐based Swin Transformer architecture for Gleason Score prediction in prostate cancer
by: Tianshuo Yang, et al.
Published: (2026)
by: Tianshuo Yang, et al.
Published: (2026)
In-vitro measurements coupled with in-silico simulations for stochastic calibration and uncertainty quantification of the mechanical response of biological materials
by: Pekedis, Mahmut
Published: (2025)
by: Pekedis, Mahmut
Published: (2025)
Robotic Ultrasound-Guided Femoral Artery Reconstruction of Anatomically-Representative Phantoms
by: Al-Zogbi, Lidia, et al.
Published: (2025)
by: Al-Zogbi, Lidia, et al.
Published: (2025)
Dose prediction via deep learning to enhance treatment planning of lung radiotherapy including simultaneous integrated boost techniques
by: Wenhua Cao, et al.
Published: (2025)
by: Wenhua Cao, et al.
Published: (2025)
Monte Carlo–based optimization of CTV‐to‐PTV margins for image‐guided VMAT prostate radiotherapy
by: Quan Chen, et al.
Published: (2026)
by: Quan Chen, et al.
Published: (2026)
Clinical VMAT machine parameter optimization for localized prostate cancer using deep reinforcement learning
by: William T. Hrinivich, et al.
Published: (2024)
by: William T. Hrinivich, et al.
Published: (2024)
Uncertainty quantification for CT dosimetry based on 10 281 subjects using automatic image segmentation and fast Monte Carlo calculations
by: Zirui Ye, et al.
Published: (2025)
by: Zirui Ye, et al.
Published: (2025)
A clustering‐based approach to address correlated features in predicting genitourinary toxicity from MRI‐guided prostate SBRT
by: Pouyan Rezapoor, et al.
Published: (2025)
by: Pouyan Rezapoor, et al.
Published: (2025)
Optimization models for needle placement in 3D-printed masks for high dose rate brachytherapy
by: Boroujeni, Nasim Mirzavand, et al.
Published: (2025)
by: Boroujeni, Nasim Mirzavand, et al.
Published: (2025)
Deep learning‐based Monte Carlo dose prediction for heavy‐ion online adaptive radiotherapy and fast quality assurance: A feasibility study
by: Rui He, et al.
Published: (2025)
by: Rui He, et al.
Published: (2025)
Deep‐learning‐based joint rigid and deformable contour propagation for magnetic resonance imaging‐guided prostate radiotherapy
by: Iris D. Kolenbrander, et al.
Published: (2024)
by: Iris D. Kolenbrander, et al.
Published: (2024)
Predicting prostate cancer recurrence using an atlas‐based tumor control probability model
by: Kazi Ridita Mahtaba, et al.
Published: (2026)
by: Kazi Ridita Mahtaba, et al.
Published: (2026)
Integrated optimization of needle paths and dwell time for individualized template‐guided interstitial brachytherapy
by: Qinglong Yao, et al.
Published: (2026)
by: Qinglong Yao, et al.
Published: (2026)
A 3D deep learning model based on MRI for predicting lymphovascular invasion in rectal cancer
by: Tangjuan Wang, et al.
Published: (2025)
by: Tangjuan Wang, et al.
Published: (2025)
Machine learning in image‐based outcome prediction after radiotherapy: A review
by: Xiaohan Yuan, et al.
Published: (2024)
by: Xiaohan Yuan, et al.
Published: (2024)
Machine‐learning‐based prediction of respiratory flow and lung volume from real‐time cardiac MRI using MR‐compatible spirometry
by: Halima Malik, et al.
Published: (2025)
by: Halima Malik, et al.
Published: (2025)
Quantifying dose perturbations in high‐risk prostate radiotherapy due to translational and rotational motion of prostate and pelvic lymph nodes
by: Karolina A. Klucznik, et al.
Published: (2024)
by: Karolina A. Klucznik, et al.
Published: (2024)
Similar Items
-
Impact of deep learning model uncertainty on manual corrections to auto-segmentation in prostate cancer radiotherapy
by: Rogowski, Viktor, et al.
Published: (2025) -
Rapid CNN‐based needle localization for automatic slice alignment in MR‐guided interventions using 3D undersampled radial white‐marker imaging
by: Jonas Frederik Faust, et al.
Published: (2024) -
Radiological mapping and uncertainty quantification by a fast Microcanonical Langevin Monte Carlo sampler
by: Pan, Lei, et al.
Published: (2026) -
Deep learning‐based dose prediction for magnetic resonance‐guided prostate radiotherapy
by: Samuel Fransson, et al.
Published: (2024) -
A novel method for pharmacokinetic parameters quantification in DCE‐MRI: Application in prostate cancer
by: Jhonalbert Aponte, et al.
Published: (2026)