The Detection of Brain Tumors User Interface for MATLAB
- Title
- The Detection of Brain Tumors User Interface for MATLAB
- Abstract
-
Background: Magnetic Resonance Imaging (MRI)
has become more popular because it improves brain and soft tissue
imaging. Medical imaging areas like MRI benefit from
Mathematical Morphology's robust framework for studying
geometric characteristics of pictures with their emergence.
Objective: This study focuses on influencing mathematical
morphology for detecting brain tumours and cancer cells in MRI
images, aiming to significantly improve diagnostic accuracy and
treatment strategies using the MATLAB graphic user interface.
Methods: The methodology encompasses three primary steps:
1) Preprocessing, which includes feature extraction and reduction;
2) Training kernel Support Vector Machines (SVM); and 3)
Processing new MRI images through the trained SVM for
predictions. This approach, rooted in a proven categorisation
technique, is further exemplified through an illustrative
algorithmic flowchart. Additionally, the article delves into
comprehensive pre-treatment processes, discusses linear and
kernel SVMs, and emphasises the importance of K-fold cross
validation to counteract overfitting.
Results: The current study on 160 MRI images using SVMs
with different Kernels showed good linear separability in feature
spaces. The results are rigorously contrasted against decade-old
methods
to prove the suggested method's superiority.
Conclusion: This study offers an innovative approach to
detecting malignant brain tumours by harnessing the capabilities
of MATLAB's graphic user interface. Given the severe
implications of brain tumours on neurological health and quality
of life and the prohibitive costs of treatments, such advancements
in diagnostic methods signify a monumental stride in medical
imaging and diagnosis. - Scientific Type
- غير معروف
- Journal volume
- vol.35,No.1
- Collaboration type
- مشترك
- Publish Date
- April 26, 2024
- Participated Universities (Publication)
-
Alnoor University
- Scopus status
- In Scopus
- Scopus index year
- 2 024
- Scopus citation score
- 0
- Clarivate status
- Not In Clarivate
- Pub. Med. status
- Not In PubMed
- Author (Publication)
- عبدالقادر فارس عبدالقادر حسن
- Journal (Publication)
-
PROCEEDING OF THE 35TH CONFERENCE OF FRUCT ASSOCIATION
- Publisher (Publication)
- IEEE Computer Society
- ISSN
- 2305-7254
- Country (Publication)
-
Russian Federation
- Country type
- عالمية
- College (Publication)
-
College of Pharmacy
- Departement (Publication)
-
Department of Pharmacy
- Media
-
Academic paper
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