3 papers
cs.CV2026
Low performing pixel correction in computed tomography with unrolled network and synthetic data training
Hongxu Yang, Levente Lippenszky, Edina Timko +2
Low performance pixels (LPP) in Computed Tomography (CT) detectors would lead to ring and streak artifacts in the reconstructed images, making them clinically unusable. In recent y…
cs.CV2025
SynBT: High-quality Tumor Synthesis for Breast Tumor Segmentation by 3D Diffusion Model
Hongxu Yang, Edina Timko, Levente Lippenszky +2
Synthetic tumors in medical images offer controllable characteristics that facilitate the training of machine learning models, leading to an improved segmentation performance. Howe…
eess.IV2025
Modality-Independent Explainable Detection of Inaccurate Organ Segmentations Using Denoising Autoencoders
Levente Lippenszky, István Megyeri, Krisztian Koos +7
In radiation therapy planning, inaccurate segmentations of organs at risk can result in suboptimal treatment delivery, if left undetected by the clinician. To address this challeng…