Copertina

Evaluating Computational Pathology Foundation Models for Prostate Cancer Grading under Distribution Shifts

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gustafsson, Fredrik K., Rantalainen, Mattias
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Image and Video Processing Computer Vision and Pattern Recognition Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Scanner-Induced Domain Shifts Undermine the Robustness of Pathology Foundation Models
di: Thiringer, Erik, et al.
Pubblicazione: (2026)

Evaluating Deep Regression Models for WSI-Based Gene-Expression Prediction
di: Gustafsson, Fredrik K., et al.
Pubblicazione: (2024)

WEEP: A method for spatial interpretation of weakly supervised CNN models in computational pathology
di: Sharma, Abhinav, et al.
Pubblicazione: (2024)

Benchmarking Pathology Foundation Models for Breast Cancer Survival Prediction
di: Gustafsson, Fredrik K., et al.
Pubblicazione: (2026)

Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer
di: Müller, Dominik, et al.
Pubblicazione: (2024)

Structured Model Pruning for Efficient Inference in Computational Pathology
di: Adnan, Mohammed, et al.
Pubblicazione: (2024)

A Mixture of Experts (MoE) model to improve AI-based computational pathology prediction performance under variable levels of histopathology image blur
di: Xiang, Yujie, et al.
Pubblicazione: (2024)

DISC: Latent Diffusion Models with Self-Distillation from Separated Conditions for Prostate Cancer Grading
di: Ho, Man M., et al.
Pubblicazione: (2024)

Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation
di: Ma, Jiabo, et al.
Pubblicazione: (2024)

Cinepro: Robust Training of Foundation Models for Cancer Detection in Prostate Ultrasound Cineloops
di: Harmanani, Mohamed, et al.
Pubblicazione: (2025)

DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks
di: Müller, Dominik, et al.
Pubblicazione: (2024)

Mask Enhanced Deeply Supervised Prostate Cancer Detection on B-mode Micro-Ultrasound
di: Zhang, Lichun, et al.
Pubblicazione: (2024)

ModalTune: Fine-Tuning Slide-Level Foundation Models with Multi-Modal Information for Multi-task Learning in Digital Pathology
di: Ramanathan, Vishwesh, et al.
Pubblicazione: (2025)

Classification of Prostate Cancer in 3D Magnetic Resonance Imaging Data based on Convolutional Neural Networks
di: Rippa, Malte, et al.
Pubblicazione: (2024)

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology
di: Zhu, Lianghui, et al.
Pubblicazione: (2025)

Ordinal Label-Distribution Learning with Constrained Asymmetric Priors for Imbalanced Retinal Grading
di: Shaik, Nagur Shareef, et al.
Pubblicazione: (2025)

EvoPS: Evolutionary Patch Selection for Whole Slide Image Analysis in Computational Pathology
di: Hashemian, Saya, et al.
Pubblicazione: (2025)

Prostate-Specific Foundation Models for Enhanced Detection of Clinically Significant Cancer
di: Lee, Jeong Hoon, et al.
Pubblicazione: (2025)

Navigating Distribution Shifts in Medical Image Analysis: A Survey
di: Su, Zixian, et al.
Pubblicazione: (2024)

C2P-GCN: Cell-to-Patch Graph Convolutional Network for Colorectal Cancer Grading
di: Paul, Sudipta, et al.
Pubblicazione: (2024)

Virchow: A Million-Slide Digital Pathology Foundation Model
di: Vorontsov, Eugene, et al.
Pubblicazione: (2023)

Multimodal Whole Slide Foundation Model for Pathology
di: Ding, Tong, et al.
Pubblicazione: (2024)

Benchmarking Histopathology Foundation Models for Ovarian Cancer Bevacizumab Treatment Response Prediction from Whole Slide Images
di: Mallya, Mayur, et al.
Pubblicazione: (2024)

Evaluating Test-Time Adaptation For Facial Expression Recognition Under Natural Cross-Dataset Distribution Shifts
di: Turnbull, John, et al.
Pubblicazione: (2026)

Knowledge-enhanced Pretraining for Vision-language Pathology Foundation Model on Cancer Diagnosis
di: Zhou, Xiao, et al.
Pubblicazione: (2024)

Causal Attribution of Model Performance Gaps in Medical Imaging Under Distribution Shifts
di: Gordaliza, Pedro M., et al.
Pubblicazione: (2025)

Improving Prostate Gland Segmentation Using Transformer based Architectures
di: Abudalou, Shatha, et al.
Pubblicazione: (2025)

ProstNFound+: A Prospective Study using Medical Foundation Models for Prostate Cancer Detection
di: Wilson, Paul F. R., et al.
Pubblicazione: (2025)

SPLICE -- Streamlining Digital Pathology Image Processing
di: Alsaafin, Areej, et al.
Pubblicazione: (2024)

IM-MoCo: Self-supervised MRI Motion Correction using Motion-Guided Implicit Neural Representations
di: Hemidi, Ziad Al-Haj, et al.
Pubblicazione: (2024)

Inpainting Pathology in Lumbar Spine MRI with Latent Diffusion
di: Hansen, Colin, et al.
Pubblicazione: (2024)

Evaluating Machine Learning-based Skin Cancer Diagnosis
di: Jain, Tanish
Pubblicazione: (2024)

AI-based Automatic Segmentation of Prostate on Multi-modality Images: A Review
di: Jin, Rui, et al.
Pubblicazione: (2024)

Cross-scale Multi-instance Learning for Pathological Image Diagnosis
di: Deng, Ruining, et al.
Pubblicazione: (2023)

RudolfV: A Foundation Model by Pathologists for Pathologists
di: Dippel, Jonas, et al.
Pubblicazione: (2024)

Leveraging Knowledge Distillation for Lightweight Skin Cancer Classification: Balancing Accuracy and Computational Efficiency
di: Islam, Niful, et al.
Pubblicazione: (2024)

Benchmarking Image Transformers for Prostate Cancer Detection from Ultrasound Data
di: Harmanani, Mohamed, et al.
Pubblicazione: (2024)

TIAViz: A Browser-based Visualization Tool for Computational Pathology Models
di: Eastwood, Mark, et al.
Pubblicazione: (2024)

Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathology
di: Remedios, Lucas W., et al.
Pubblicazione: (2024)

Spatial-temporal Hierarchical Reinforcement Learning for Interpretable Pathology Image Super-Resolution
di: Chen, Wenting, et al.
Pubblicazione: (2024)