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How far is the automated 3-D segmentation of Brain MRI efficient compared to manual segmentation?

  • We are doing a project on automated 3-D segmentation of brain MRI using MATLAB. We would like to know the extent to which "Surf" commands are efficient in producing reliable segmented 3-D image. The accuracy level, how much it is better compared to manual segmentation. We need statistical detail, kindly help us....

  • Answer:

    This correspondence deals with the development of an automated 3-D segmentation of Brain MRI. The proposal is a model-based approach for accurate, robust, and automated tissue segmentation of brain MRI data of single as well as multiple magnetic resonance sequences. The main contribution of this study is that we employ an edge-based geodesic active contour for the segmentation task by integrating both image edge geometry and voxel statistical homogeneity into a novel hybrid geometric–statistical feature to regularize contour convergence and extract complex anatomical structures. We validate the accuracy of the segmentation results on simulated brain MRI scans of both single T1-weighted and multiple T1/ T2/PD-weighted sequences. When compared to a current stateof- the-art region based level-set segmentation formulation, our white matter and gray matter segmentation resulted in significantly higher accuracy levels with a mean improvement in Dice similarity indexes. Thus the development of the project is done using MATLAB simulation for results. A Hybrid Automated 3D Segmentation in Brain MRI ----------------------------------------... Advantages of a MRI scan • MRI scanners are good at looking at the non-bony parts or "soft tissues" of the body. In particular, the brain, spinal cord and nerves are seen much more clearly with MRI than with regular x-rays and CAT scans. • Also, muscles, ligaments and tendons are seen quite well so that MRI scans are commonly used to look at knees and shoulders following injuries. • A MRI scanner uses no x-rays or other radiation. • A disadvantage of MRI is it’s higher cost compared to a regular x-ray or CAT scan. Also, CAT scans are frequently better at looking at the bones that MRI.

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This correspondence deals with the development of an automated 3-D segmentation of Brain MRI. The proposal is a model-based approach for accurate, robust, and automated tissue segmentation of brain MRI data of single as well as multiple magnetic resonance sequences. The main contribution of this study is that we employ an edge-based geodesic active contour for the segmentation task by integrating both image edge geometry and voxel statistical homogeneity into a novel hybrid geometric–statistical feature to regularize contour convergence and extract complex anatomical structures. We validate the accuracy of the segmentation results on simulated brain MRI scans of both single T1-weighted and multiple T1/ T2/PD-weighted sequences. When compared to a current stateof- the-art region based level-set segmentation formulation, our white matter and gray matter segmentation resulted in significantly higher accuracy levels with a mean improvement in Dice similarity indexes. Thus the development of the project is done using MATLAB simulation for results. A Hybrid Automated 3D Segmentation in Brain MRI ----------------------------------------… Advantages of a MRI scan • MRI scanners are good at looking at the non-bony parts or "soft tissues" of the body. In particular, the brain, spinal cord and nerves are seen much more clearly with MRI than with regular x-rays and CAT scans. • Also, muscles, ligaments and tendons are seen quite well so that MRI scans are commonly used to look at knees and shoulders following injuries. • A MRI scanner uses no x-rays or other radiation. • A disadvantage of MRI is it’s higher cost compared to a regular x-ray or CAT scan. Also, CAT scans are frequently better at looking at the bones that MRI.

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