54 citations · 63 across the 3 of their papers we have counts for
5 papers
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…
Deep Learning Fetal Ultrasound Video Model Match Human Observers in Biometric Measurements
Szymon Płotka, Adam Klasa, Aneta Lisowska +4
Objective. This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, bipar…
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…
Spontaneous preterm birth prediction using convolutional neural networks
Tomasz Włodarczyk, Szymon Płotka, Przemysław Rokita +4
An estimated 15 million babies are born too early every year. Approximately 1 million children die each year due to complications of preterm birth (PTB). Many survivors face a life…
Estimation of preterm birth markers with U-Net segmentation network
Tomasz Włodarczyk, Szymon Płotka, Tomasz Trzciński +4
Preterm birth is the most common cause of neonatal death. Current diagnostic methods that assess the risk of preterm birth involve the collection of maternal characteristics and tr…