@inbook{05c3182c631b4159b582da9cc020cc41,
title = "A Multi-task Approach Using Positional Information for Ultrasound Placenta Segmentation",
abstract = "Automatic segmentation of the placenta in fetal ultrasound (US) is challenging due to its high variations in shape, position and appearance. Convolutional neural networks (CNN) are the state-of-the-art in medical image segmentation and have already been applied successfully to extract the placenta in US. However, the performance of CNNs depends highly on the availability of large training sets which also need to be representative for new unseen data. In this work, we propose to inform the network about the variability in the data distribution via an auxiliary task to improve performances for under representative training sets. The auxiliary task has two objectives: (i) enlarging of the training set with easily obtainable labels, and (ii) including more information about the variability of the data in the training process. In particular, we use transfer learning and multi-task learning to incorporate the placental position in a U-Net architecture. We test different models for the segmentation of anterior and posterior placentas in fetal US. Our results suggest that these placenta types represent different distributions. By including the position of the placenta as an auxiliary task, the segmentation accuracy for both anterior and posterior placentas is improved when the specific type of placenta is not included in the training set.",
author = "Zimmer, {Veronika A.} and Alberto Gomez and Emily Skelton and Nooshin Ghavami and Robert Wright and Lei Li and Jacqueline Matthew and Hajnal, {Joseph V.} and Schnabel, {Julia A.}",
year = "2020",
doi = "10.1007/978-3-030-60334-2_26",
language = "English",
isbn = "9783030603335",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "264--273",
editor = "Yipeng Hu and Roxane Licandro and Noble, {J. Alison} and Jana Hutter and Andrew Melbourne and Stephen Aylward and {Abaci Turk}, Esra and {Torrents Barrena}, Jordina and {Torrents Barrena}, Jordina",
booktitle = "Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis - 1st International Workshop, ASMUS 2020, and 5th International Workshop, PIPPI 2020, Held in Conjunction with MICCAI 2020, Proceedings",
address = "Germany",
note = "1st International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2020, and the 5th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2020, held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 ; Conference date: 04-10-2020 Through 08-10-2020",
}