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Brain tumor segmentation and its area calculation in brain MR images using K-mean clustering and Fuzzy C-mean algorithm

机译:使用K均值聚类和模糊C平均算法脑MR图像脑MR图像中脑肿瘤分割及其区域计算

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This paper deals with the implementation of Simple Algorithm for detection of range and shape of tumor in brain MR images. Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and they have different Characteristics and different treatment. As it is known, brain tumor is inherently serious and life-threatening because of its character in the limited space of the intracranial cavity (space formed inside the skull). Most Research in developed countries show that the number of people who have brain tumors were died due to the fact of inaccurate detection. Generally, CT scan or MRI that is directed into intracranial cavity produces a complete image of brain. This image is visually examined by the physician for detection & diagnosis of brain tumor. However this method of detection resists the accurate determination of stage & size of tumor. To avoid that, this project uses computer aided method for segmentation (detection) of brain tumor based on the combination of two algorithms. This method allows the segmentation of tumor tissue with accuracy and reproducibility comparable to manual segmentation. In addition, it also reduces the time for analysis. At the end of the process the tumor is extracted from the MR image and its exact position and the shape also determined. The stage of the tumor is displayed based on the amount of area calculated from the cluster.
机译:本文涉及实施简单算法,用于检测脑MR图像中肿瘤的范围和形状。肿瘤是体内任何部位的组织的不受控制的生长。肿瘤的类型不同,它们具有不同的特性和不同的治疗方法。众所周知,由于其在颅内腔的有限空间(在头骨内形成的空间)中的性格,脑肿瘤本质上是严重的并且危及生命的危及性。大多数发达国家的研究表明,由于检测不准确而导致患有脑肿瘤的人数被死亡。通常,被引入颅内腔的CT扫描或MRI产生了脑的完整形象。该图像是由医生目视检查的,用于检测和诊断脑肿瘤。然而,这种检测方法抵抗了肿瘤阶段和大小的准确测定。为避免这种项目,基于两种算法的组合,使用计算机辅助方法进行脑肿瘤的分割(检测)。该方法允许肿瘤组织与可与手动分割相当的准确性和再现性分段。此外,它还减少了分析时间。在该过程结束时,从MR图像提取肿瘤,并且其确切位置也确定。肿瘤的阶段基于来自群集计算的面积的量来显示。

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