Segmentation and tracking of lung nodules via graph-cuts incorporating shape prior and motion from 4D CT

Author:

Cha Jungwon1,Farhangi Mohammad Mehdi1,Dunlap Neal2,Amini Amir A.1

Affiliation:

1. Medical Imaging Laboratory; University of Louisville; Louisville KY 40292 USA

2. Department of Radiation Oncology; Brown Cancer Center; University of Louisville; Louisville KY 40202 USA

Publisher

Wiley

Subject

General Medicine

Reference32 articles.

1. Armato IIISG McLennan G Bidaut L Data From LIDC-IDRI. The Cancer Imaging Archive http://doi.org/10.7937/K9/TCIA.2015.LO9QL9SX 2015

2. Soft computing approach to 3D lung nodule segmentation in CT;Badura;Comput Biol Med.,2014

3. Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods;Beichel;Med Phys.,2012

4. An experimental comparison of min-cut/max-ow algorithms for energy minimization in vision;Boykov;IEEE Trans Pattern Anal Mach Intell,2004

5. Fast approximate energy minimization via graph cuts;Boykov;IEEE Trans Pattern Anal Mach Intell.,2001

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