Ivana Isgum
8 papers · 2021–2026 · 1 venue · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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Academic Marathon · Sprint
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Interdisciplinary Bridge · Silver
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Taxonomy Completionist
(16)
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Trend Setter
Venues
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Research topics
Machine Learning
(5)
Computer Vision
(4)
Deep Learning
(4)
Healthcare & Medicine
(3)
Analysis
(3)
Application Areas
(3)
Clinical
(3)
Learning Types · Deep Learning
(3)
Domain-Specific
(2)
Processing
(2)
Artificial Intelligence
(1)
Architectures
(1)
Core AI
(1)
Learning Types · Machine Learning
(1)
Models
(1)
Keywords
implicit neural representation
(2)
motion estimation
(1)
3d volume
(1)
medical image segmentation
(1)
magnetic resonance imaging
(1)
geometric prior
(1)
multi-objective optimization
(1)
deformable image registration
(1)
generative adversarial network
(1)
temporal consistency
(1)
neural field
(1)
centerline extraction
(1)
multiple sclerosis
(1)
image encoder
(1)
image reconstruction
(1)
sparse sampling
(1)
multi-task learning
(1)
attenuation correction
(1)
intravascular ultrasound
(1)
meta learning
(1)
Papers
CyclePhase: Robust phase detection in cardiovascular imaging through cyclic motion estimation
MIDL 2026
Neural fields for tissue attenuation curve reconstruction in sparsely sampled time-resolved CT
MIDL 2025
Accelerating physics-informed neural fields for fast CT perfusion analysis in acute ischemic stroke
MIDL 2024
REINDIR: Repeated Embedding Infusion for Neural Deformable Image Registration
MIDL 2024
Deformable Image Registration with Geometry-informed Implicit Neural Representations
MIDL 2023
Generative Adversarial Networks for Coronary CT Angiography Acquisition Protocol Correction with Explicit Attenuation Constraints
MIDL 2023
MultiTask Learning for accelerated-MRI Reconstruction and Segmentation of Brain Lesions in Multiple Sclerosis
MIDL 2023
Untangling the Small Intestine in 3D cine-MRI using Deep Stochastic Tracking
MIDL 2021