Cover Image

PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fröhlich, Alek, Ramos, Thiago, Cabello, Gustavo, Buzatto, Isabela, Izbicki, Rafael, Tiezzi, Daniel
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Image and Video Processing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Rel-UNet: Reliable Tumor Segmentation via Uncertainty Quantification in nnU-Net
by: Ziaee, Seyed Sina, et al.
Published: (2025)

General Intelligent Imaging and Uncertainty Quantification by Deterministic Diffusion Model
by: Fan, Weiru, et al.
Published: (2024)

Fine-tuned Transformer Models for Breast Cancer Detection and Classification
by: Osman, Showkat, et al.
Published: (2025)

GRAPHITE: Graph-Based Interpretable Tissue Examination for Enhanced Explainability in Breast Cancer Histopathology
by: Mondol, Raktim Kumar, et al.
Published: (2025)

Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification
by: Lei, Shuge, et al.
Published: (2024)

Neural variational Data Assimilation with Uncertainty Quantification using SPDE priors
by: Beauchamp, Maxime, et al.
Published: (2024)

Neural Orientation Distribution Fields for Estimation and Uncertainty Quantification in Diffusion MRI
by: Consagra, William, et al.
Published: (2023)

Conformalized Generative Bayesian Imaging: An Uncertainty Quantification Framework for Computational Imaging
by: Ekmekci, Canberk, et al.
Published: (2025)

FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantification
by: Shen, Yiqing, et al.
Published: (2024)

Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
by: Thrun, Solveig, et al.
Published: (2025)

Fully Automated Assessment of Cardiac Coverage in Cine Cardiovascular Magnetic Resonance Images using an Explainable Deep Visual Salient Region Detection Model
by: Nabavi, Shahabedin, et al.
Published: (2022)

Adversarially Robust Feature Learning for Breast Cancer Diagnosis
by: Hao, Degan, et al.
Published: (2024)

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge
by: Li, Hongwei Bran, et al.
Published: (2024)

VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction
by: Sun, Zijun, et al.
Published: (2025)

Novel AI-Based Quantification of Breast Arterial Calcification to Predict Cardiovascular Risk
by: Dapamede, Theodorus, et al.
Published: (2025)

Optimizing MV CBCT Imaging Protocols Using NTCP and Secondary Cancer Risk: A Multi-Site Study in Breast, Pelvic, and Head & Neck Radiotherapy
by: Duong, Thanh Tai, et al.
Published: (2025)

Breast Cancer Classification with Enhanced Interpretability: DALAResNet50 and DT Grad-CAM
by: Liu, Suxing
Published: (2023)

STA-Risk: A Deep Dive of Spatio-Temporal Asymmetries for Breast Cancer Risk Prediction
by: Zhou, Zhengbo, et al.
Published: (2025)

Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer
by: Shaik, Abdul Samad, et al.
Published: (2025)

Task-Based Adaptive Transmit Beamforming for Efficient Ultrasound Quantification
by: Nolan, Oisín, et al.
Published: (2026)

An Artificial Intelligence Model for Early Stage Breast Cancer Detection from Biopsy Images
by: Chaudhary, Neil, et al.
Published: (2025)

Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction
by: Wen, Jeffrey, et al.
Published: (2024)

UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs
by: Mehta, Raghav, et al.
Published: (2025)

Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
by: Hoppe, Frederik, et al.
Published: (2024)

Subgroup Performance of a Commercial Digital Breast Tomosynthesis Model for Breast Cancer Detection
by: Brown-Mulry, Beatrice, et al.
Published: (2025)

How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning
by: Wang, Yuanyuan, et al.
Published: (2024)

Comparison of ConvNeXt and Vision-Language Models for Breast Density Assessment in Screening Mammography
by: Molina-Román, Yusdivia, et al.
Published: (2025)

A Hybrid Feature Fusion Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Sample Using Gated Recurrent Unit and Uncertainty Quantification
by: Akter, Maksuda, et al.
Published: (2024)

Towards Early Detection: AI-Based Five-Year Forecasting of Breast Cancer Risk Using Digital Breast Tomosynthesis Imaging
by: Dorster, Manon A., et al.
Published: (2025)

Uncertainty-Gated Deformable Network for Breast Tumor Segmentation in MR Images
by: Zhang, Yue, et al.
Published: (2025)

WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer
by: Gao, Yifan, et al.
Published: (2025)

Attention-Map Augmentation for Hypercomplex Breast Cancer Classification
by: Lopez, Eleonora, et al.
Published: (2023)

A Comprehensive Framework for Uncertainty Quantification of Voxel-wise Supervised Models in IVIM MRI
by: Casali, Nicola, et al.
Published: (2025)

DUCPS: Deep Unfolding the Cauchy Proximal Splitting Algorithm for B-Lines Quantification in Lung Ultrasound Images
by: Yang, Tianqi, et al.
Published: (2024)

A European Multi-Center Breast Cancer MRI Dataset
by: Müller-Franzes, Gustav, et al.
Published: (2025)

Joint Stream: Malignant Region Learning for Breast Cancer Diagnosis
by: Rehman, Abdul, et al.
Published: (2024)

LeqMod: Adaptable Lesion-Quantification-Consistent Modulation for Deep Learning Low-Count PET Image Denoising
by: Xia, Menghua, et al.
Published: (2024)

Uncertainty Quantification for Cardiac Shape Reconstruction with Deep Signed Distance Functions via MCMC methods
by: Verhülsdonk, Jan, et al.
Published: (2026)

A Deep Learning Approach to Multi-Fiber Parameter Estimation and Uncertainty Quantification in Diffusion MRI
by: Consagra, William, et al.
Published: (2024)

Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis
by: Molchanova, Nataliia, et al.
Published: (2024)