Medical Tomography Imaging is normally used to identify certain conditions on certain tissue to get further data about diseases diagnosis. MRI (Magnetic Resonance Imaging), X-Ray, CT-Scan are the established tomography modalities in medicine. They are used to capture the detail tissue imaging for Doctors diagnosis purposes. Radiation effect is one of the concerned issues on this tomography modality. Hence, some research on developing alternative non-invasive tomography modality such as, EIT (Electrical Impedance Tomography), ERT (Electrical Resistance Tomography), ECVT (Electrical Capacitance Volume Tomography), etc. that is also feasible for medical used, has been developed. In addition, under-sampling MRI , X-Ray or CT-Scan is also a possible solution for less invasive medical tomography. This under sampling imaging is intended to reduce the scanning time, hence reducing the radiation effect. This research focuses on proposing an under-sampling MRI Imaging algorithm design based on compressive sensing framework. It is intended to provide good quality MRI image in the reconstruction and recovery point of view subject to less measurement information. Compressive Sensing itself is widely used to solve inverse problems that are closely related to under-sampling measurements projection. Hence it is promising to be adopted on under-sampling MRI Imaging.

Medical Tomography, MRI, Imaging, Image Reconstructing, Image Recovery, Compressive Sensing

• Dr. Endra, S.Kom., M.T.

• Muhammad Edo Syahputra, S.T., M.Kom.

• Dr. Nur Afny Catur Andryani, S.Si., M.Sc.