Juampablo Heras Rivera
  • Home
  • Publications
  • Experience
  • Contact Me
  • Recent & Upcoming Talks
    • Example Talk
  • Publications
    • Bias Mitigation for Brain Age Prediction via Age Delta Correlation Loss
    • BTReport: A Framework for Brain Tumor Radiology Report Generation with Clinically Relevant Features
    • Can You Trust Your Model? Constructing Uncertainty Approximations Guaranteeing Validity of Glioma Segmentation Explanations
    • Clinical Interpretability of Deep Learning Segmentation Through Shapley-Derived Agreement and Uncertainty Metrics
    • CoRe-BT: A Multimodal Radiology-Pathology-Text Benchmark for Robust Brain Tumor Typing
    • DisQ-HNet: A Disentangled Quantized Half-UNet for Interpretable Multimodal Image Synthesis Applications to Tau-PET Synthesis from T1 and FLAIR MRI
    • Interpretable Tau-PET Synthesis from Multimodal T1-Weighted and FLAIR MRI Using Partial Information Decomposition Guided Disentangled Quantized Half-UNet
    • Clinically-Informed Preprocessing Improves Stroke Segmentation in Low-Resource Settings
    • Here comes the explanation: A shapley perspective on multi-contrast medical image segmentation
    • How We Won the ISLES'24 Challenge by Preprocessing
    • Real-time nonlinear inversion of magnetic resonance elastography with operator learning
    • An ensemble approach for brain tumor segmentation and synthesis
    • Improving glioma segmentation in low-resolution domains with transfer learning
    • Isles' 24: Improving final infarct prediction in ischemic stroke using multimodal imaging and clinical data
    • Re-DiffiNet: modeling discrepancies in tumor segmentation using diffusion models
    • Benefits and challenges of data-driven models for velocity/pressure-gradient correlations in turbulent flows.
    • Development of models for the velocity-pressure gradient correlations in incompressible wall-bounded planar turbulent flows using multiple linear regression
    • Uncertainty quantification for high explosive reactant and product equations of state
    • On the Contribution of Data Errors in DNS Data-Driven VPG Correlation Models
  • Projects
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Blog
    • 📈 Communicate your results effectively with the best data visualizations
    • 👩🏼‍🏫 Teach academic courses
    • ✅ Manage your projects
    • index
  • Experience
  • Teaching
    • Learn JavaScript
    • Learn Python
  • Contact

Here comes the explanation: A shapley perspective on multi-contrast medical image segmentation

Jan 1, 2025·
Tianyi Ren
,
Juampablo Heras Rivera
,
Hitender Oswal
,
Yutong Pan
,
Agamdeep Chopra
,
Jacob Ruzevick
,
Mehmet Kurt
· 0 min read
PDF Preprint
Type
Preprint
Publication
arXiv preprint arXiv:2504.04645
Last updated on Jan 1, 2025
Preprint
← Clinically-Informed Preprocessing Improves Stroke Segmentation in Low-Resource Settings Jan 1, 2025
How We Won the ISLES'24 Challenge by Preprocessing Jan 1, 2025 →

Published with Hugo Blox Builder — the free, open source website builder that empowers creators.