Name
Abstract | ||
|---|---|---|
Ensuring image quality control (QC) for data acquired in a multimodality context offers substantial advantages for both multi-level and multipoint analysis. Although a variety of neuroimage analysis algorithms exist, the tasks of multimodal neuroimaging data QC and integration remain challenging because image quality can be affected by numerous factors. Here, we discuss the challenges of the QC and integration of neuroimaging data and provide two examples of often-neglected and potentially under-appreciated problems related to the QC of diffusion tensor imaging (DTI) data and to their integration with other modalities. Specifically, we illustrate the challenges of (1) DTI/MRI co-registration and (2) scanner vibration artifacts, both being representative examples of difficulties involving both data QC and its integration. Additionally, we highlight the need for automatic methods which can address neuroimaging data QC which allows for its successful integration. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-21843-4_15 | DATA INTEGRATION IN THE LIFE SCIENCES, DILS 2015 |
Keywords | Field | DocType |
Neuroimaging, Data quality control, Data integration, Diffusion tensor imaging, 3D visualization | Modalities,Data integration,Data mining,Diffusion MRI,Visualization,Computer science,Image quality,Scanner,Neuroimaging | Conference |
Volume | ISSN | Citations |
9162 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sumiko Abe | 1 | 1 | 0.37 |
| Andrei Irimia | 2 | 57 | 10.84 |
| John D Van Horn | 3 | 316 | 28.50 |