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Ultrasound Medical Images Classification Based on Deep Learning Algorithms: A Review

Authors Names :   Fairoz Q. Kareem   1     Adnan Mohsin Abdulazeez   2  

1  Affiliation :  IT Department. Technical College of Informatics – Akre, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

    Email :  fairoz.kareem@dpu.edu.krd

2  Affiliation :  Computer Engineering, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

    Email :  adnan.mohsin@dpu.edu.krd

Doi   :   https://doi.org/10.54216/FPA.030102

Received November 10, 2020 Revised February 3, 2021 Accepted March 14, 2021

Abstract :

With the development of technology and smart devices in the medical field, the computer system has become an essential part of this development to learn devices in the medical field. One of the learning methods is deep learning (DL), which is a branch of machine learning (ML). The deep learning approach has been used in this field because it is one of the modern methods of obtaining accurate results through its algorithms, and among these algorithms that are used in this field are convolutional neural networks (CNN) and recurrent neural networks (RNN). In this paper we reviewed what have researchers have done in their researches to solve fetal problems, then summarize and carefully discuss the applications in different tasks identified for segmentation and classification of ultrasound images. Finally, this study discussed the potential challenges and directions for applying deep learning in ultrasound image analysis.  

Keywords :

Fetal Brain Deformities , Deep Learning Algorithms , Ultrasonic Images , Classification.

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Cite this Article as :
Fairoz Q. Kareem , Adnan Mohsin Abdulazeez, Ultrasound Medical Images Classification Based on Deep Learning Algorithms: A Review, Fusion: Practice and Applications, Vol. 3 , No. 1 , (2021) : 29-42 (Doi   :  https://doi.org/10.54216/FPA.030102)