6533b871fe1ef96bd12d17fa
RESEARCH PRODUCT
Review on Machine Learning Based Lesion Segmentation Methods from Brain MR Images
Evgin GoceriEsther DuraMelih Gunaysubject
Lesion segmentationmedicine.diagnostic_testbusiness.industryComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMagnetic resonance imagingPattern recognitionImage segmentationMachine learningcomputer.software_genre030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineComputer-aided diagnosisHistogrammedicineUnsupervised learningSegmentationComputer visionArtificial intelligencebusinesscomputer030217 neurology & neurosurgerydescription
Brain lesions are life threatening diseases. Traditional diagnosis of brain lesions is performed visually by neuro-radiologists. Nowadays, advanced technologies and the progress in magnetic resonance imaging provide computer aided diagnosis using automated methods that can detect and segment abnormal regions from different medical images. Among several techniques, machine learning based methods are flexible and efficient. Therefore, in this paper, we present a review on techniques applied for detection and segmentation of brain lesions from magnetic resonance images with supervised and unsupervised machine learning techniques.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-12-01 | 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA) |