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20162026
most citedAdversarial training and dilated convolutions for brain MRI segmentation

23 citations · 70 across the 17 of their papers we have counts for

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14 papers · 1 filter

eess.IV2025

Artificial Intelligence-Based Classification of Spitz Tumors

Ruben T. Lucassen, Marjanna Romers, Chiel F. Ebbelaar +10

Spitz tumors are diagnostically challenging due to overlap in atypical histological features with conventional melanomas. We investigated to what extent AI models, using histologic…

eess.IV2025

A Spatially-Aware Multiple Instance Learning Framework for Digital Pathology

Hassan Keshvarikhojasteh, Mihail Tifrea, Sibylle Hess +2

Multiple instance learning (MIL) is a promising approach for weakly supervised classification in pathology using whole slide images (WSIs). However, conventional MIL methods such a…

eess.IV2025

Adaptive Prototype Learning for Multimodal Cancer Survival Analysis

Hong Liu, Haosen Yang, Federica Eduati +2

Leveraging multimodal data, particularly the integration of whole-slide histology images (WSIs) and transcriptomic profiles, holds great promise for improving cancer survival predi…

eess.IV2024

World of Forms: Deformable Geometric Templates for One-Shot Surface Meshing in Coronary CT Angiography

Rudolf L. M. van Herten, Ioannis Lagogiannis, Jelmer M. Wolterink +8

Deep learning-based medical image segmentation and surface mesh generation typically involve a sequential pipeline from image to segmentation to meshes, often requiring large train…

eess.IV2024

Tissue Cross-Section and Pen Marking Segmentation in Whole Slide Images

Ruben T. Lucassen, Willeke A. M. Blokx, Mitko Veta

Tissue segmentation is a routine preprocessing step to reduce the computational cost of whole slide image (WSI) analysis by excluding background regions. Traditional image processi…

eess.IV2021

Optimized Automated Cardiac MR Scar Quantification with GAN-Based Data Augmentation

Didier R. P. R. M. Lustermans, Sina Amirrajab, Mitko Veta +2

Background: The clinical utility of late gadolinium enhancement (LGE) cardiac MRI is limited by the lack of standardization, and time-consuming postprocessing. In this work, we tes…