Medical Imaging R&D

Team ADISL has been a regular at Journal of Magnetic Resonance Imaging (JMRI), Journal of Computer Assisted Tomography (JCAT), The International Society for Magnetic Resonance in Medicine (ISMRM) and European Society for Magnetic Resonance in Medicine and Biology (ESMRMB).

We have in-house developed implementations of following scientific protocols:

Diffusion Tensor Imaging (DTI)

DTI allows one to obtain quantitative information about the three-dimensional anisotropic diffusion of water molecules in biological tissues. An important potential application of DTI is the visualization of anatomical connections between individual parts of the brain. This issue is difficult, as one has to infer continuity of fiber orientation from voxel to voxel.

DTI Tractography

Tractography utilizes the voxelwise diffusion anisotropy and the orientation of diffusion ellipsoid in reconstructing fiber tracts. A grouping of voxels along a fiber tract gives rise to the associated fiber bundles delineating the related axonal communication structure.



Following fiber bundles have been shown in images: [1] Corpus Callosum (CC) and its subdivisions, [2] Tapetum (TP), [3] Inferior Longitudinal Fasciculus (ILF), [4] Uncinate Fasciculus (UNC), [5] Inferior fronto-occipital fasciculus (IFO), [6] Optic Pathways (OP), [7] Superior Longitudinal Fasciculus (SLF), [8] Arcuate Fasciculus (AF), [9] Fornix (FX), [10] Cingulum (CG), [11] Anterior Thalamic Radiation (ATR), [(12] Superior Thalamic Radiation (STR), [13] Posterior Thalamic Radiation (PTR), [14] Corticospinal/Corticopontine Tract (CST/CPT), [15] Medial Lemniscus (ML), [16] Superior Cerebellar Peduncle (SCP), [17] Middle Cerebellar Peduncle (MCP), and [18] Inferior Cerebellar Peduncle (ICP).

Accurate analysis of in-vivo MRS and high resolution NMR signals

Our expertise lies in two related areas,namely modeling of NMR signal and data processing. Worth mentioning being [1] a new method based on Bezier curve for baseline correction of NMR data in the frequency domain [2] a frequency-domain least squares based iterative method for quantifying in vivo 1H MRS data including short echo spectra.

Perfusion

In-house developed methodologies to estimate pre-contrast tissue parameter (T10) using fast spin echo (FSE) and quantification of physiological and hemodynamic parameters with leakage correction using T1-weighted dynamic contrast enhanced (DCE) perfusion imaging.