NDLI: Detection and localisation of multiple brain tumours by object counting and elimination

Content Provider	IET Digital Library
Author	Nasor, Mohamed Obaid, Walid
Abstract	Brain cancer is a major health problem that affects the lives of many people. Clinicians depend on their medical knowledge to analyse laboratory test results and clinical information extracted manually from medical images, to identify the essential characteristics of tumours such as size, shape, and location. The accurate diagnosis of brain tumours is very essential for deciding the most appropriate treatment protocols and procedures. Apart from being tedious, slow and time-consuming manual segmentation of brain image scans is also prone to human error. In order to enhance the accuracy and reliability of the diagnosis of brain tumours, rigorous image processing and segmentation is required. In this study the authors present an automated image segmentation method for detecting and localising multiple brain tumours of different sizes and intensities by using a technique of object counting coupled with an evaluation process. The object counting technique were carried out using multiple binary images with different threshold values, and the evaluation process was based on assessment criteria of specific tumour parameters. Different magnetic resonance images with multiple tumours were used for testing the proposed method. The results indicated that the proposed method is effective in detecting and localising multiple true tumours in the brain.
Starting Page	615
Ending Page	620
Page Count	6
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 4, Mar (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0071
Journal	IET Image Processing
Publisher Date	2019-12-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automated Image Segmentation Method Biology And Medical Computing Biomedical Magnetic Resonance Imaging Biomedical MRI Brain Brain Cancer Brain Image Scans Cancer Computer Vision And Image Processing Technique Evaluation Process Image Segmentation Laboratory Test Magnetic Resonance Imaging Image Medical Image Medical Image Processing Medical Knowledge Medical Magnetic Resonance Imaging And Spectroscopy Multiple Binary Image Multiple Brain Tumour Detection Multiple Brain Tumour Localisation Object Counting Object Detection Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Rigorous Image Processing Spectroscopy Time-consuming Manual Segmentation Treatment Protocol Tumour Parameter Tumours
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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