8 citations · 14 across the 12 of their papers we have counts for
12 papers
X-Splat: Gaussian Splatting for 3D CBCT Generation from Single Panoramic Radiograph
Tomasz Szczepański, Szymon Płotka, Michal K. Grzeszczyk +2
Generating a 3D dental volume from a single panoramic radiograph (PXR) could provide a low-radiation alternative to Cone-Beam Computed Tomography (CBCT), but the problem is highly…
LumiMotion: Improving Gaussian Relighting with Scene Dynamics
Joanna Kaleta, Piotr Wójcik, Kacper Marzol +3
In 3D reconstruction, the problem of inverse rendering, namely recovering the illumination of the scene and the material properties, is fundamental. Existing Gaussian Splatting-bas…
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…
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…
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…
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…
MISS: Multiclass Interpretable Scoring Systems
Michal K. Grzeszczyk, Tomasz Trzciński, Arkadiusz Sitek
In this work, we present a novel, machine-learning approach for constructing Multiclass Interpretable Scoring Systems (MISS) - a fully data-driven methodology for generating single…
Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load
Michal K. Grzeszczyk, Paulina Adamczyk, Sylwia Marek +8
The effectiveness of digital treatments can be measured by requiring patients to self-report their state through applications, however, it can be overwhelming and causes disengagem…
BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video
Szymon Płotka, Michal K. Grzeszczyk, Robert Brawura-Biskupski-Samaha +4
Predicting fetal weight at birth is an important aspect of perinatal care, particularly in the context of antenatal management, which includes the planned timing and the mode of de…
POTHER: Patch-Voted Deep Learning-Based Chest X-ray Bias Analysis for COVID-19 Detection
Tomasz Szczepański, Arkadiusz Sitek, Tomasz Trzciński +1
A critical step in the fight against COVID-19, which continues to have a catastrophic impact on peoples lives, is the effective screening of patients presented in the clinics with…
FetalNet: Multi-task Deep Learning Framework for Fetal Ultrasound Biometric Measurements
Szymon Płotka, Tomasz Włodarczyk, Adam Klasa +3
In this paper, we propose an end-to-end multi-task neural network called FetalNet with an attention mechanism and stacked module for spatio-temporal fetal ultrasound scan video ana…
Convolutional Neural Networks in Orthodontics: a review
Szymon Płotka, Tomasz Włodarczyk, Ryszard Szczerba +5
Convolutional neural networks (CNNs) are used in many areas of computer vision, such as object tracking and recognition, security, military, and biomedical image analysis. This rev…