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Supervised Machine Learning Methods and Hyperspectral Imaging Techniques Jointly Applied for Brain Cancer Classification
- Source :
- Sensors, Vol 21, Iss 3827, p 3827 (2021), Sensors (Basel, Switzerland), Sensors, Volume 21, Issue 11
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- Hyperspectral imaging techniques (HSI) do not require contact with patients and are non-ionizing as well as non-invasive. As a consequence, they have been extensively applied in the medical field. HSI is being combined with machine learning (ML) processes to obtain models to assist in diagnosis. In particular, the combination of these techniques has proven to be a reliable aid in the differentiation of healthy and tumor tissue during brain tumor surgery. ML algorithms such as support vector machine (SVM), random forest (RF) and convolutional neural networks (CNN) are used to make predictions and provide in-vivo visualizations that may assist neurosurgeons in being more precise, hence reducing damages to healthy tissue. In this work, thirteen in-vivo hyperspectral images from twelve different patients with high-grade gliomas (grade III and IV) have been selected to train SVM, RF and CNN classifiers. Five different classes have been defined during the experiments: healthy tissue, tumor, venous blood vessel, arterial blood vessel and dura mater. Overall accuracy (OACC) results vary from 60% to 95% depending on the training conditions. Finally, as far as the contribution of each band to the OACC is concerned, the results obtained in this work are 3.81 times greater than those reported in the literature.
- Subjects :
- tumor
Computer science
hyperspectral imaging
brain
education
convolutional neural network
Healthy tissue
TP1-1185
Machine learning
computer.software_genre
01 natural sciences
Biochemistry
Convolutional neural network
Field (computer science)
Article
Analytical Chemistry
Brain cancer
03 medical and health sciences
0302 clinical medicine
Humans
support vector machine
neurosurgery
Electrical and Electronic Engineering
Instrumentation
Brain tumor surgery
business.industry
Brain Neoplasms
Chemical technology
010401 analytical chemistry
Hyperspectral imaging
Atomic and Molecular Physics, and Optics
0104 chemical sciences
Random forest
Support vector machine
machine learning
classification
Artificial intelligence
Neural Networks, Computer
Supervised Machine Learning
business
computer
030217 neurology & neurosurgery
random forest
Subjects
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 21
- Issue :
- 3827
- Database :
- OpenAIRE
- Journal :
- Sensors
- Accession number :
- edsair.doi.dedup.....61d7461e1e7f67fcac547dc73d78306d