Funder
co-financed by the European Union with the European regional development fund and by the Normandie Regional Council via the MoNoMaD project
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Radiology Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering
Reference25 articles.
1. Yu Y, Decazes P, Lapuyade-Lahorgue J, Gardinb I, Vera P, Ruan S (2018) Semi-automatic lymphoma detection and segmentation using fullyconditional random fields. Comput Med Imaging Graph 70:1–7
2. Black QC, Grills IS, Kestin LL, Wong CY, Wong JW, Martinez AA, Yan D (2004) Defining a radiotherapy target with positron emission tomography. Int J Radiat Oncol Biol Phys 60(4):1272–1282
3. Nestle U, Kremp S, Schaefer-Schuler A, Sebastian-Welsch C, Hellwig D, Rübe C, Kirsch CM (2004) Comparison of different methods for delineation of18F-FDG PET-positive tissue for target volume definition in radiotherapy ofpatients with non-small cell lung cancer. J Nucl Med 46(8):1342–1348
4. Tylski P, Stute S, Grotus N, Doyeux K, Hepdey S, Gardin I, Vanderlinden B, Buvat I (2010) Comparative assessment of methods for estimating tumorvolume and standardized uptake value in (18) F-FDG PET. J Nucl Med 51:268–276
5. Desbordes P, Petitjean C, Ruan S (2014) 3D Automated lymphoma segmentation in PET images based on cellular automata. In: 4th International conference on image processing theory, tools and applications (IPTA)
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