Copertina

Mitigating False Predictions In Unreasonable Body Regions

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ulrich, Constantin, Knobloch, Catherine, Holzschuh, Julius C., Wald, Tassilo, Rokuss, Maximilian R., Zenk, Maximilian, Fischer, Maximilian, Baumgartner, Michael, Isensee, Fabian, Maier-Hein, Klaus H.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Image and Video Processing Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation
di: Ulrich, Constantin, et al.
Pubblicazione: (2023)

Promptable Longitudinal Lesion Segmentation in Whole-Body CT
di: Kirchhoff, Yannick, et al.
Pubblicazione: (2025)

Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures
di: Kirchhoff, Yannick, et al.
Pubblicazione: (2024)

Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting
di: Rokuss, Maximilian, et al.
Pubblicazione: (2024)

Data-Centric Strategies for Overcoming PET/CT Heterogeneity: Insights from the AutoPET III Lesion Segmentation Challenge
di: Kovacs, Balint, et al.
Pubblicazione: (2024)

MedNeXt-v2: Scaling 3D ConvNeXts for Large-Scale Supervised Representation Learning in Medical Image Segmentation
di: Roy, Saikat, et al.
Pubblicazione: (2025)

From FDG to PSMA: A Hitchhiker's Guide to Multitracer, Multicenter Lesion Segmentation in PET/CT Imaging
di: Rokuss, Maximilian, et al.
Pubblicazione: (2024)

A Unified Framework for Foreground and Anonymization Area Segmentation in CT and MRI Data
di: Nohel, Michal, et al.
Pubblicazione: (2025)

Divide and Conquer: A Large-Scale Dataset and Model for Left-Right Breast MRI Segmentation
di: Rokuss, Maximilian, et al.
Pubblicazione: (2025)

The Missing Piece: A Case for Pre-Training in 3D Medical Object Detection
di: Eckstein, Katharina, et al.
Pubblicazione: (2025)

MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation
di: Roy, Saikat, et al.
Pubblicazione: (2023)

An OpenMind for 3D medical vision self-supervised learning
di: Wald, Tassilo, et al.
Pubblicazione: (2024)

Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution
di: Fischer, Maximilian, et al.
Pubblicazione: (2024)

Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning
di: Fischer, Maximilian, et al.
Pubblicazione: (2025)

Towards Interactive Lesion Segmentation in Whole-Body PET/CT with Promptable Models
di: Rokuss, Maximilian, et al.
Pubblicazione: (2025)

Large Scale Supervised Pretraining For Traumatic Brain Injury Segmentation
di: Ulrich, Constantin, et al.
Pubblicazione: (2025)

RadioActive: 3D Radiological Interactive Segmentation Benchmark
di: Ulrich, Constantin, et al.
Pubblicazione: (2024)

Unlocking the Potential of Digital Pathology: Novel Baselines for Compression
di: Fischer, Maximilian, et al.
Pubblicazione: (2024)

Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes
di: Fischer, Maximilian, et al.
Pubblicazione: (2024)

Scaling nnU-Net for CBCT Segmentation
di: Isensee, Fabian, et al.
Pubblicazione: (2024)

nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation
di: Isensee, Fabian, et al.
Pubblicazione: (2024)

Image Rotation Angle Estimation: Comparing Circular-Aware Methods
di: Woehrer, Maximilian
Pubblicazione: (2026)

A Modified da Vinci Surgical Instrument for OCE based Elasticity Estimation with Deep Learning
di: Neidhardt, Maximilian, et al.
Pubblicazione: (2024)

Input Data Adaptive Learning (IDAL) for Sub-acute Ischemic Stroke Lesion Segmentation
di: Götz, Michael, et al.
Pubblicazione: (2024)

Gut decisions based on the liver: A radiomics approach to boost colorectal cancer screening
di: Hinterberger, Anna, et al.
Pubblicazione: (2025)

LesionLocator: Zero-Shot Universal Tumor Segmentation and Tracking in 3D Whole-Body Imaging
di: Rokuss, Maximilian, et al.
Pubblicazione: (2025)

Understanding Benefits and Pitfalls of Current Methods for the Segmentation of Undersampled MRI Data
di: Morshuis, Jan Nikolas, et al.
Pubblicazione: (2025)

Segmentation-guided MRI reconstruction for meaningfully diverse reconstructions
di: Morshuis, Jan Nikolas, et al.
Pubblicazione: (2024)

HyperSpace: Hypernetworks for spacing-adaptive image segmentation
di: Joutard, Samuel, et al.
Pubblicazione: (2024)

Resolution Enhancement of Scanning Electron Micrographs using Artificial Intelligence
di: Reclik, Tom, et al.
Pubblicazione: (2024)

CUTE-MRI: Conformalized Uncertainty-based framework for Time-adaptivE MRI
di: Fischer, Paul, et al.
Pubblicazione: (2025)

Field-Space Autoencoder for Scalable Climate Emulators
di: Meuer, Johannes, et al.
Pubblicazione: (2026)

AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics
di: Dippel, Jonas, et al.
Pubblicazione: (2024)

Sea-Undistort: A Dataset for Through-Water Image Restoration in High Resolution Airborne Bathymetric Mapping
di: Kromer, Maximilian, et al.
Pubblicazione: (2025)

Anomaly Detection in Medical Imaging -- A Mini Review
di: Tschuchnig, Maximilian E., et al.
Pubblicazione: (2021)

Identifying Alzheimer's Disease Prediction Strategies of Convolutional Neural Network Classifiers using R2* Maps and Spectral Clustering
di: Tinauer, Christian, et al.
Pubblicazione: (2025)

Enhancing Synthetic CT from CBCT via Multimodal Fusion: A Study on the Impact of CBCT Quality and Alignment
di: Tschuchnig, Maximilian, et al.
Pubblicazione: (2025)

nnInteractive: Redefining 3D Promptable Segmentation
di: Isensee, Fabian, et al.
Pubblicazione: (2025)

On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting
di: Wagner, Fabian, et al.
Pubblicazione: (2022)

Hybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification
di: Tschuchnig, Maximilian, et al.
Pubblicazione: (2025)