Image Fusion of MRI and CT Scan for Brain Tumor Detection Using VGG-19
Authors:-Professor Kirti Digholkar, Shreyas Depura, Adwait Mali, Vedant Latthe, Rohan Patil
Abstract-For a patient’s prognosis, the careful examination of image bio-analytics, including Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) imaging, is crucial for the patient’s tumor detection. Moreover, interpreting these images manually remains challenging owing to the required expertise and time needed to properly analyze the images. To address this issue, we propose an image improvement model that enhances the accuracy of MRI and CT scans using Wavelet- based fusion and the VGG-19 architecture. Image fusion, or the merging of medical images, synergistically uses and adapts the various modalities’ strengths and weaknesses. In our research, we apply the Wavelet approach to MRI and CT images by splitting them into frequency sub-bands. Structural details are important for the image’s low-frequency LL band. The VGG- 19 network which consists of several convolutional layers and pooling layers is then used to merge the LL bands and form the fused images. Our method undergoes a series of preprocessing, feature extraction, and fusion stages on brain MRI and CT scans. This method saves time for medical practitioners and enables efficient tumor identification through automation, improving the overall quality of patient care.
