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In this chapter, we will look more closely at a specific application of CNNs, namely segmentation of normal brains from magnetic resonance images (MRI).
Deng and Bentley [65] aimed segmentation of normal heart sounds and detection of murmurs.
In this section, the performance of the proposed PIGFCM is evaluated for the segmentation of normal and pathological brain MRI volumes.
This paper proposes a new fuzzy approach for the automatic segmentation of normal and pathological brain magnetic resonance imaging (MRI) volumetric datasets.
As there are publically available standard benchmark datasets of normal synthetic and real human brain MRI volumes with known ground truth, our first series of experiments are directed to the automatic segmentation of normal brain tissues.
A two stage statistical model based on texture and shape for fully automatic choroidal segmentation of normal and pathologic eyes obtained by a 1060 nm optical coherence tomography (OCT) system is developed.
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Although RG has been successful with the segmentation of the normal lungs in both human and small animal studies, pathological lung tissue caused by pulmonary infections can make automatic lung segmentation from CT scans very challenging.
Ulterior developments of the algorithm for the automatic segmentation of peri-vascular tissue (e.g. texture based segmentation) and discrimination of normal artery wall (e.g. additional geometrical features) would allow for a fully automated assessment of images and thus complete IVOCT pullbacks.
This study reveals the problem segmentation of abnormal and normal tissues from MRI images using gray-level co-occurrence matrix (GLC M feature extraction and probabilistic neural network (PNN) classifier.
Using TTP value of voxels between (TTPmedian − 3 sec) and TTPmedian as the criteria for the segmentation of brain tissue with normal perfusion after CSF removal and preliminary vessel removal, the segmented normal brain parenchyma was compatible with the clinical and angiographic findings in all 30 cases.
In summary, Mesp2 is required for the normal segmentation of somites and generation of the rostro-caudal polarity of somites.
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