To develop a 3D multi-contrast IVW protocol with 0.5-mm isotropic resolution and a scan time of 5 min per sequence.
Materials and methods
Pre-contrast T1w VISTA, DANTE prepared PDw VISTA, SNAP, and post-contrast T1w VISTA were accelerated using cartesian undersampling with target ordering method (CUSTOM) and self-supporting tailored k-space estimation for parallel imaging reconstruction (STEP). CUSTOM + STEP IVW was compared to full-sample IVW, SENSE-accelerated IVW, and CUSTOM + zero-filled Fourier reconstruction in normal volunteers and subjects with intracranial atherosclerotic disease (ICAD). Image quality, vessel delineation, CSF suppression, and blood suppression were compared.
Results
CUSTOM + STEP vessel wall delineation was comparable to full-sample IVW and better than SENSE IVW for vessel wall delineation on T1w VISTA and luminal contrast on SNAP. Average image quality and wall depiction were significantly improved using STEP reconstruction compared with zero-filled Fourier reconstruction, with no significant difference in CSF or blood suppression.
Conclusions
CUSTOM + STEP allowed multi-contrast 3D 0.5-mm isotropic IVW within 30 min. Although some quantitative and qualitative scores for CUSTOM − STEP were lower than fully sampled IVW, CUSTOM + STEP provided comparable vessel wall delineation as full-sample IVW and was superior to SENSE. CUSTOM + STEP IVW was well tolerated by patients and showed good delineation of ICAD plaque.
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The Web has evolved into a dominant digital medium for conducting many types of online transactions such as shopping, paying
bills, making travel plans, etc. Such transactions typically involve a number of steps spanning several Web pages. For sighted
users these steps are relatively straightforward to do with graphical Web browsers. But they pose tremendous challenges for
visually impaired individuals. This is because screen readers, the dominant assistive technology used by visually impaired
users, function by speaking out the screen’s content serially. Consequently, using them for conducting transactions can cause
considerable information overload. But usually one needs to browse only a small fragment of a Web page to do a step of a transaction
(e.g., choosing an item from a search results list). Based on this observation this paper presents a model-directed transaction
framework to identify, extract and aurally render only the “relevant” page fragments in each step of a transaction. The framework
uses a process model to encode the state of the transaction and a concept model to identify the page fragments relevant for
the transaction in that state. We also present algorithms to mine such models from click stream data generated by transactions
and experimental evidence of the practical effectiveness of our models in improving user experience when conducting online
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