IOP Conference Series Materials Science and Engineering · 2018 · 36 citations · 11 references
MedicineOncologyRadiologyBiomedical ImagingDiagnostic ImagingNeuro-oncologyBrain TumorsImage AnalysisImage SegmentationMedical Image AnalysisMedical ImagingTumor DetectionAutomatic SegmentationBrain Tumor DiagnosisImage-based Tumor DetectionMedical Image SegmentationTumor Segmentation
Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient's life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.
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Automatic tumor segmentation using knowledge-based techniques
Matthew C. Clark, Lawrence Hall, Dmitry B. Goldgof et al. · IEEE Transactions on Medical Imaging · 1998 · 463 citations