A Survey on Automated CAD System of Liver Tumor using US Images

• Published in: 2022 7th International Conference on Communication and Electronics Systems (ICCES) pp. 1515 - 1520
• Main Authors: Uplaonkar, Deepak S, Virupakshappa, Rangayya, Patil, Nagabhushan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22.06.2022
• Subjects: discrete wavelet transformation and artificial neural network; Feature extraction; Image segmentation; Level set; Liver; Speckle; speckle noise; Ultrasonic imaging; ultrasound; Visualization
• DOI: 10.1109/ICCES54183.2022.9835914

Visual analysis of human organs is currently one of the most active subjects under study in the field of computer vision. The ability of a machine to analyse human organs is a critical aspect in its development. Medical imaging is a procedure that allows clinicians to examine a part of the human body that is not naturally visible. In Medical Image Processing, analysis and visualization application allows for quantitative analysis and visualization of a variety of medical imaging modalities. The objective of this survey is to present an overview of current computer-assisted diagnosis approaches for detecting tumor lesions using ultrasound images. Research papers published between 2019 and 2021 from various standard databases were considered in preparation for the survey. The paper initially discusses the various speckle reduction approaches on ultrasound images, then various segmentation approaches based on level set are discussed. Finally various approaches for discrete wavelet transformation-based feature extraction and neural network-based classification are also discussed. The review gives an insight on the work carried out so far for reduction of speckle noise in ultrasound image, level set-based segmentation methods, discrete wavelet transformation-based feature extraction methods and artificial neural network based classification methods.