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20172026
most citedA large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations

50 citations · 104 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

Dense Temporal Contrast Synthesis via Conditioned Latent Transport

Smriti Joshi, Apostolia Tsirikoglou, Daniel M. Lang +15

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for breast cancer management, but reliance on gadolinium-based contrast agents (GBCAs) restricts use in…

cs.CV2024★ 50 cited

A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations

Lidia Garrucho, Kaisar Kushibar, Claire-Anne Reidel +30

Artificial Intelligence (AI) research in breast cancer Magnetic Resonance Imaging (MRI) faces challenges due to limited expert-labeled segmentations. To address this, we present a…

cs.CV2021

How to cheat with metrics in single-image HDR reconstruction

Gabriel Eilertsen, Saghi Hajisharif, Param Hanji +3

Single-image high dynamic range (SI-HDR) reconstruction has recently emerged as a problem well-suited for deep learning methods. Each successive technique demonstrates an improveme…

cs.CV2021★ 2 cited

Ensembles of GANs for synthetic training data generation

Gabriel Eilertsen, Apostolia Tsirikoglou, Claes Lundström +1

Insufficient training data is a major bottleneck for most deep learning practices, not least in medical imaging where data is difficult to collect and publicly available datasets a…

cs.CV2017★ 38 cited

Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications

Apostolia Tsirikoglou, Joel Kronander, Magnus Wrenninge +1

We present an overview and evaluation of a new, systematic approach for generation of highly realistic, annotated synthetic data for training of deep neural networks in computer vi…