Efficient parametric encoding scheme for white matter fiber bundles

TRAKO: Efficient Transmission of Tractography Data for Visualization

Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow for efficient storage, transfer, and visualization. We present TRAKO, a new data format based on the Graphics Layer Transmission Format (glTF) that enables immediate graphical and hardware-accelerated processing. We integrate a state-of-the-art compression technique for vertices, streamlines, and attached scalar and property data. We then compare TRAKO to existing tractography storage methods and provide a detailed evaluation on eight datasets. TRAKO can achieve data reductions of over 28x without loss of statistical significance when used to replicate analysis from previously published studies.

QFib: Fast and Efficient Brain Tractogram Compression

Diffusion MRI fiber tracking datasets can contain millions of 3D streamlines, and their representation can weight tens of gigabytes of memory. These sets of streamlines are called tractograms and are often used for clinical operations or research. Their size makes them difficult to store, visualize, process or exchange over the network. We propose a new compression algorithm well-suited for tractograms, by taking advantage of the way streamlines are obtained with usual tracking algorithms. Our approach is based on unit vector quantization methods combined with a spatial transformation which results in low compression and decompression times, as well as a high compression ratio. For instance, a 11.5GB tractogram can be compressed to a 1.02GB file and decompressed in 11.3 seconds. Moreover, our method allows for the compression and decompression of individual streamlines, reducing the need for a costly out-of-core algorithm with heavy datasets. Last, we open a way toward on-the-fly compression and decompression for handling larger datasets without needing a load of RAM (i.e. in-core handling), faster network exchanges and faster loading times for visualization or processing.

Magnetic resonance imaging DTI-FT study on schizophrenic patients with typical negative first symptoms

Magnetic resonance imaging (MRI) with diffusion-tensor imaging (DTI) together with a white matter fiber tracking (FT) technique was used to assess different brain white matter structures and functionalities in schizophrenic patients with typical first negative symptoms. In total, 30 schizophrenic patients with typical first negative symptoms, comprising an observation group were paired 1:1 according to gender, age, right-handedness, and education, with 30 healthy individuals in a control group. Individuals in each group underwent routine MRI and DTI examination of the brain, and diffusion-tensor tractography (DTT) data were obtained through whole brain analysis based on voxel and tractography. The results were expressed by fractional anisotropy (FA) values. The schizophrenic patients were evaluated using a positive and negative symptom scale (PANSS) as well as a Global Assessment Scale (GAS). The results of the study showed that routine MRIs identified no differences between the two groups. However, compared with the control group, the FA values obtained by DTT from the deep left prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and part of the corpus callosum were significantly lower in the observation group (P<0.05). The PANSS positive scale value in the observation group averaged 7.7±1.5, and the negative scale averaged 46.6±5.9, while the general psychopathology scale averaged 65.4±10.3, and GAS averaged 53.8±19.2. The Pearson statistical analysis, the left deep prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and the FA value of part of the corpus callosum in the observation group was negatively correlated with the negative scale (P<0.05), and positively correlated with GAS (P<0.05). In conclusion, a decrease in the FA values of the left deep prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and part of the corpus callosum may be associated with schizophrenia with typical first negative symptoms and the application of MRI DTI-FT can improve diagnostic accuracy.