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eess.IV2026

Mamba Goes HoME: Hierarchical Soft Mixture-of-Experts for 3D Medical Image Segmentation

Szymon Płotka, Gizem Mert, Maciej Chrabaszcz +2

In recent years, artificial intelligence has significantly advanced medical image segmentation. Nonetheless, challenges remain, including efficient 3D medical image processing acro…

eess.IV2025

GEPAR3D: Geometry Prior-Assisted Learning for 3D Tooth Segmentation

Tomasz Szczepański, Szymon Płotka, Michal K. Grzeszczyk +5

Tooth segmentation in Cone-Beam Computed Tomography (CBCT) remains challenging, especially for fine structures like root apices, which is critical for assessing root resorption in…

eess.IV2025

RegScore: Scoring Systems for Regression Tasks

Michal K. Grzeszczyk, Tomasz Szczepański, Pawel Renc +4

Scoring systems are widely adopted in medical applications for their inherent simplicity and transparency, particularly for classification tasks involving tabular data. In this wor…

eess.IV2024

TabMixer: Noninvasive Estimation of the Mean Pulmonary Artery Pressure via Imaging and Tabular Data Mixing

Michal K. Grzeszczyk, Przemysław Korzeniowski, Samer Alabed +3

Right Heart Catheterization is a gold standard procedure for diagnosing Pulmonary Hypertension by measuring mean Pulmonary Artery Pressure (mPAP). It is invasive, costly, time-cons…

eess.IV2024

Let Me DeCode You: Decoder Conditioning with Tabular Data

Tomasz Szczepański, Michal K. Grzeszczyk, Szymon Płotka +5

Training deep neural networks for 3D segmentation tasks can be challenging, often requiring efficient and effective strategies to improve model performance. In this study, we intro…

eess.IV2024

Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results

Kelly Payette, Céline Steger, Roxane Licandro +64

Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and th…