Book chapter · Conference paper
Automatic Segmentation of Abdominal Fat in MRI-Scans, Using Graph-Cuts and Image Derived Energies
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
University of Copenhagen3
Office of the President, Administration, Technical University of Denmark4
Statistics and Data Analysis, Department of Applied Mathematics and Computer Science, Technical University of Denmark5
For many clinical studies changes in the abdominal distribution of fat is an important measure. However, the segmentation of abdominal fat in MRI scans is both difficult and time consuming using manual methods. We present here an automatic and flexible software package, that performs both bias field correction and segmentation of the fat into superficial and deep subcutaneous fat as well as visceral fat with the spinal compartment removed.
Assessment when comparing to the gold standard - CT-scans - shows a correlation and bias comparable to manual segmentation. The method is flexible by tuning the image-derived energies used for the segmentation, allowing the method to be applied to other body parts, such as the thighs.
| Language: | English |
|---|---|
| Publisher: | Springer |
| Year: | 2017 |
| Pages: | 109-120 |
| Proceedings: | 20th Scandinavian Conference on Image Analysis |
| Series: | Lecture Notes in Computer Science |
| Journal subtitle: | 20th Scandinavian Conference, Scia 2017, Tromsø, Norway, June 12–14, 2017, Proceedings, Part II |
| ISBN: | 3319591282 , 3319591290 , 9783319591285 and 9783319591292 |
| ISSN: | 03029743 |
| Types: | Book chapter and Conference paper |
| DOI: | 10.1007/978-3-319-59129-2_10 |
| ORCIDs: | Christensen, Anders Nymark , Larsen, Rasmus , Conradsen, Knut and Dahl, Vedrana Andersen |
