Name
Title | ||
|---|---|---|
Learning Based Segmentation of CT Brain Images: Application to Postoperative Hydrocephalic Scans. |
Abstract | ||
|---|---|---|
Objective: Hydrocephalus is a medical condition in which there is an abnormal accumulation of cerebrospinal fluid (CSF) in the brain. Segmentation of brain imagery into brain tissue and CSF [before and after surgery, i.e., preoperative (pre-op) versus postoperative (post-op)] plays a crucial role in evaluating surgical treatment. Segmentation of pre-op images is often a relatively straightforward ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TBME.2017.2783305 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Image segmentation,Dictionaries,Training,Brain,Computed tomography,Machine learning,Hospitals | Training set,Dictionary learning,Pattern recognition,Computer science,Segmentation,Hydrocephalus,Artificial intelligence,Pixel,Feature based,Memory footprint,Test procedures | Journal |
Volume | Issue | ISSN |
65 | 8 | 0018-9294 |
Citations | PageRank | References |
3 | 0.39 | 24 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Venkateswararao Cherukuri | 1 | 11 | 3.52 |
| Peter Ssenyonga | 2 | 3 | 0.73 |
| Benjamin C. Warf | 3 | 3 | 0.73 |
| Abhaya V. Kulkarni | 4 | 3 | 0.73 |
| Vishal Monga | 5 | 679 | 57.73 |
| Steven J. Schiff | 6 | 142 | 22.45 |