Computer-Aided Monitoring of Fetus Health From Ultrasound Images: A Review

Year 2022, , 283 - 302, 31.12.2022

Deniz Atas , Yonca Bayrakdar Yılmaz

https://doi.org/10.26650/acin.1099106

Abstract

Computer aided diagnostic methods have been helping medical experts for monitoring fetus health for many
years. The use of new methods has made a positive effect in monitoring the health of fetus as well as the diagnosis
of anomalies. This study first introduces the indicators for identifying anomalies in fetus and gives basic
information about computer-based methods such as traditional image processing, machine learning and deep
learning. Then an overview of existing studies which use novel techniques on monitoring fetus health and
anomaly detection from ultrasound images is given. Finally, the main challenges of novel techniques and future
directions of research on computer-aided monitoring of fetus health are summarized.

Keywords

Computer-Aided Diagnosis, Fetus Health, Deep Learning, Machine Learning, Image Processing

Ultrason Görüntülerinden Fetus Sağlığının Bilgisayar Destekli Takibi: Bir İnceleme

Abstract

Bilgisayar destekli tanı yöntemleri, tıp uzmanlarına yıllardır fetüs sağlığını izlemek için yardımcı olmaktadır.
Yeni yöntemlerin kullanılması, fetüsün sağlığının izlenmesinin yanı sıra anomalilerin tanısında da olumlu bir
etki yaratmıştır. Bu çalışma ilk olarak fetüste anomalileri tanımlamak için kullanılan göstergeleri tanıtır ve
geleneksel görüntü işleme, makine öğrenimi ve derin öğrenme gibi bilgisayar tabanlı yöntemler hakkında temel
bilgiler verir. Daha sonra, ultrason görüntülerinden fetüs sağlığının izlenmesi ve anomali tespitinde yeni teknikler
kullanan mevcut çalışmalara genel bir bakış verilmiştir. Son olarak, fetüs sağlığının bilgisayar destekli izlenmesi
üzerine güncel tekniklerle ilgili ana zorluklar ve araştırmaların gelecekteki yönü özetlenmiştir.

Keywords

Bilgisayar Destekli Tanı, Fetüs Sağlığı, Derin Öğrenme, Makine Öğrenmesi, Görüntü İşleme

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