Name
Abstract | ||
|---|---|---|
We present a novel visualization framework, AnaFe, targeted at observing changes in the spleen over time through multiple image-derived features. Accurate monitoring of progressive changes is crucial for diseases that result in enlargement of the organ. Our system is comprised of multiple linked views combining visualization of temporal 3D organ data, related measurements, and features. Thus it enables the observation of progression and allows for simultaneous comparison within and between the subjects. AnaFe offers insights into the overall distribution of robustly extracted and reproducible quantitative imaging features and their changes within the population, and also enables detailed analysis of individual cases. It performs similarity comparison of temporal series of one subject to all other series in both sick and healthy groups. We demonstrate our system through two use case scenarios on a population of 189 spleen datasets from 68 subjects with various conditions observed over time. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TVCG.2016.2598463 | IEEE Trans. Vis. Comput. Graph. |
Keywords | Field | DocType |
Diseases,Shape,Data visualization,Volume measurement,Visual analytics,Imaging | Population,Computer vision,Data visualization,Visualization,Computer science,Volume measurement,Visual analytics,Artificial intelligence,Quantitative imaging,Computer graphics,Radiomics | Journal |
Volume | Issue | ISSN |
23 | 1 | 1077-2626 |
Citations | PageRank | References |
1 | 0.34 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ievgeniia Gutenko | 1 | 1 | 0.68 |
| Konstantin Dmitriev | 2 | 9 | 1.96 |
| Arie Kaufman | 3 | 33 | 4.13 |
| matthew a barish | 4 | 3 | 2.07 |