Comparison of image processing techniques for segmentations of images in healthcare in speed of executions

Abstract

Advancements in computing technologies have resulted in high performing low cost computers which have been exploited in healthcare. IPTs (Image Processing Techniques) have been important and widely used for medical image analysis. Images obtained from medical imaging modalities have been analyzed for obtaining quantitative information or data where segmentations play an important part. Image segmentations in computer vision are applied to various fields including medical imaging, video surveillances, object detections/ recognitions, IRs (Image Retrievals) and automatic traffic control systems. Medical image segmentation approaches are utilised for diagnosis and treatment planning as they extract useful information fro pictures and with the basic goal of improving digital picture analyses. However, assessing performances of segmentation algorithms has become a must in order for obtaining appropriate results. This study highlights different techniques used in segmentations of medical images with a comparison of their performances in segmentations. The base objective of this study is to examine segmentation algorithms in a detailed way and thus promote further and deeper researches in combinations of approaches for effective and accurate segmentation of human body parts from medical images.