MRIDetect: Improved MRI Image Brain Tumor Detection Implementing Techniques for Piecewise Linear Transformation

Effective treatment of brain tumors greatly depends on timely intervention and prompt identification of the disease. Most traditional image processing approaches have a particular challenge in augmenting the detection of tumors on MRI images, which may result in misdiagnosis or no diagnosis at all. In this research, we focus on enhancing finding a brain tumors MRI images through the use in piecewise linear transformation techniques. The proposed method detects and defines certain intensity values and adds custom linear transformations so that the contrast of tumor tissues with other brain structures is maximized. A large number of experiments conducted with the proposed method of MRI images improved that the detection of tumors is increased, hence improving the diagnosis. MRI images that need better detection features can employ this method for accurate evaluation. The findings suggest that utilizing piecewise linear transformation in MRI imaging can effectively enhance the detection of brain tumors and regions of interest in an effortless approach. Several methods encompassing line stretch, bi-linear stretch and global stretching collectively, or various linear piecewise techniques, stretch the contrast of images depicting the brain with tumors so that the most features possible may be observed. These methods are critical as they allow clearer visibility of fine details that would be otherwise not observable. When it comes to techniques for expanding an image's intensity range, contrast stretching and linear contrast stretching change. While the two methods apply linear transformations to certain intensity ranges, bi-linear transform stretching uses two ranges. The tuning of the intensity values is known as contrast adjustment. These methods improve the visibility of the tumor aiding in its detection and evaluation by increasing the contrast between tumor tissues and surrounding brain structures. These techniques greatly aid medical imaging in diagnosing issues with improved precision. The MRI images of brain tumors processed using these methods showed remarkable clarity improvements, verifying the techniques’ significance in medical imaging.