Segmentation of Brain Tumor using Multiple Threshold Technique

Ashalatha M E, M. Holi, Shubha V. Patel, Deepashri K M
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Abstract

Radiology use medical imaging techniques to comprehend the structure and physiological functions of the body in bothhealthy and diseased subjects. A non-invasive method for viewing internal body structures can be performed by using magneticresonance imaging (MRI). MRI characterizes soft tissue more accurately than other imaging methods like CT. In the currentstudy, space-occupying lesions are visualized using MRI imaging. Slices of MRI data are used to analyze lesions. Single sliceanalysis is inappropriate to determine the lesion’s size and volume. Hence, the MRI sequence is used to segment the lesions.Following segmentation, we view the MRI 2D image in 3D to look for lesions, or aberrant tissue, in the brain. The lesion isthen visualized by performing clipping. This research suggests segmenting brain tumors automatically and even provides a3D visualization for a more thorough study. Here, a space-occupying lesion is segmented from a T2 weighted Flair sequenceof MR images in DICOM format, and by employing the segmented volume, 3D rendering and clipping are made possible
基于多阈值技术的脑肿瘤分割
放射学使用医学成像技术来了解健康和患病受试者的身体结构和生理功能。磁共振成像(MRI)是一种非侵入性的观察身体内部结构的方法。MRI比CT等其他成像方法更准确地表征软组织。在目前的研究中,占位性病变是通过MRI成像可视化的。MRI数据切片用于分析病变。单片分析不适合确定病变的大小和体积。因此,MRI序列用于分割病变。在分割之后,我们在3D中查看MRI 2D图像以寻找大脑中的病变或异常组织。然后通过剪接观察病变。这项研究建议对脑肿瘤进行自动分割,甚至为更深入的研究提供3d可视化。在这里,占位性病变以DICOM格式从MR图像的T2加权Flair序列中分割出来,通过使用分割的体积,可以实现3D渲染和剪切
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