Brain Tumor Detection Quantification MRI DCIOM IMAGES - MATLAB PROJECTS CODE


Nowadavs, the inside situation could be obtained by medical machines, such as Computed Tomography (U), Magnetic Resonance Imaging (MRI) scanner, etc. These noninvasive diagnosis means increase the precision of the diagnoses, at the same time decrease the pain of the patients. Brain tumor diagnoses benefits from these devises very much. In the brain MR image, the tumor is shown clearly. For the treatment, the ph?sician also needs the quantification of the tumr area. This requires the abnormal part in the imge to be segmenred accurately; afrenvard the segmented area can be measured. This task could not be handled by hnnds totally.

7he computer can give great help during this procedure. In this pper we introduce one system to perform the task mentioned above. In this system. the brain tiinwr MR image is segmented semiautomatically. One deformable model-based method is adapted in the system And by the graphic user interface, the segmentation can be intervened by user interactively of real time. Therefore in the computer-aided diagnosis (CAD) system, the expert hand work for image segmentation is the gold standard. But it is too time consuming, tedious, and further more, maybe difficult for the doctor to handle it. The automatic image segmentation by computer is often doubted by the expert since the doctor's knowledge and experience is more important in the interested area determining, and computer could not simulate all the doctor's actions in the diagnosis.

So the CAD system should find a good balance between manual manner and automatic manner in the segmentation procedure. To reach this goal, the system should implement the algorithm of the segmentation, which could get the most precise result as possible. In the other hand, the system should adapt god interactive mechanism that segmentation could be under the user's control and give the feedback in the real time. This paper describes our CAD system, Med-Volumeter, which is such a general-purpose segmentation quantification, visua~ization tool.