Jurica Sprem

Orcid: 0000-0002-9165-0847

According to our database1, Jurica Sprem authored at least 11 papers between 2017 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
EchoLVFM: One-Step Video Generation via Latent Flow Matching for Echocardiogram Synthesis.
CoRR, March, 2026

2025
EchoAdapter: Adapting Pretrained Image Diffusion Models for Cardiac Ultrasound Video Generation.
Proceedings of the Deep Generative Models - 5th MICCAI Workshop, 2025

From Transthoracic to Transesophageal: Cross-Modality Generation Using LoRA Diffusion.
Proceedings of the Simplifying Medical Ultrasound - 6th International Workshop, 2025

2024
A Data Augmentation Pipeline to Generate Synthetic Labeled Datasets of 3D Echocardiography Images using a GAN.
CoRR, 2024

Graph Convolutional Neural Networks for Automated Echocardiography View Recognition: A Holistic Approach.
CoRR, 2024

2023
A Domain Translation Framework With an Adversarial Denoising Diffusion Model to Generate Synthetic Datasets of Echocardiography Images.
IEEE Access, 2023

Deep Learning for Multi-Level Detection and Localization of Myocardial Scars Based on Regional Strain Validated on Virtual Patients.
IEEE Access, 2023

Graph Convolutional Neural Networks for Automated Echocardiography View Recognition: A Holistic Approach.
Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023

Transesophageal Echocardiography Generation Using Anatomical Models.
Proceedings of the Data Augmentation, Labelling, and Imperfections - Third MICCAI Workshop, 2023

2022
A Data Augmentation Pipeline to Generate Synthetic Labeled Datasets of 3D Echocardiography Images Using a GAN.
IEEE Access, 2022

2017
Classification of coronary artery calcifications according to motion artifacts in chest CT using a convolutional neural network.
Proceedings of the Medical Imaging 2017: Image Processing, 2017


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