Paper Info
Title
A Review: Image Analysis Techniques to Improve Labeling Accuracy of Medical Image Classification.
Abstract
Medical images contain the Region of Interest (ROI) from the affected area in human body and provide useful information to support clinical decision-making for diagnostics as well as the treatment planning. Unfortunately, medical image data may contain noise, missing values, inhomogeneous ROI that may give inaccurate diagnostic. Therefore, image analysis techniques are needed to improve the quality of an image. Then, features extraction task will be performed to produce best feature of images which leads to better classification result for accurate diagnostic. Many techniques have been used for image analysis. However, limited review have been done in categorize the list of related techniques for each image analysis task in medical imaging application. Thus, the aims of this paper is to gather and present general overview of image analysis task and their techniques in order to inspire researcher, pathologist or radiologist to adapt it when analyzing different types of medical image. The current study of image analysis task was summarized and discussed in this paper.
Year
DOI
Venue
2018
10.1007/978-3-319-72550-5_29
RECENT ADVANCES ON SOFT COMPUTING AND DATA MINING (SCDM 2018)
Keywords
Field
DocType
Image analysis technique,Medical image,Image classification
Categorization,Computer science,Medical imaging,Radiation treatment planning,Artificial intelligence,Region of interest,Missing data,Contextual image classification,Machine learning
Conference
Volume
ISSN
Citations 
700
2194-5357
1
PageRank 
References 
Authors
0.39
20
3
Name
Order
Citations
PageRank
Mazniha Berahim110.72
Noor Azah Samsudin2154.54
Shelena Soosay Nathan310.72