| Scholar Name | Manan Nanavati |
| Department | Instrumentation & Control |
| Reseach Area | Image Processing |
| Supervisor Name | Dr. M.K.Shah |
| Title | Decision Support System for Diagnosis and Treatment Planning of Lower Back Pain using Image Fusion Technique |
| Abstract | Lower back pain, often known as LBP, is a widespread disorder and also one of the reason for cause of disability that impacts a large number of individuals globally. Accurate diagnosis and proper treatment planning are essential for the successful control of LBP. Medical imaging technologies have made considerable advancements in recent years, providing clinicians with a vast amount of valuable information. But so far there do not exists any single modality which gives every necessary information and visualization which is an important factor in accurate diagnosis. Hence in past years, researchers have proposed the concept of image fusion in which necessary information and features from multiple images are merged together resulting in single representative image. The concept of image fusion was preliminary used for satellite imaging purpose but in past two decades it has been introduced in field of medical and has yielded some promising and noteworthy outcomes. Image fusion can be performed using either spatial domain or frequency domain techniques. Frequency domain approaches are the most preferable option due to their ability to enhance the quality of image edges. Image fusion enhances the information content of the resulting images, making them more suited for classification tasks compared to the individual input images. This study introduces a decision support system that aims to improve and assist the diagnosis and treatment planning for Lower Back Pain (LBP) focusing on detection of bulged disc by taking fused image as input obtained through implemented image fusion techniques. newline newlineAbstract The proposed work combines the multiple modalities of magnetic resonance imaging (MRI) scans i.e. MR T1 and MR T2, using various image fusion algorithms. The fused image consists of combined information on single image that offers valuable information into the structural and pathological aspects of the spine, enabling clinicians to make critical decisions. |