PuSH - Publikationsserver des Helmholtz Zentrums München

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1.
Baur, C.* ; Denner, S.* ; Wiestler, B.* ; Navab, N.* & Albarqouni, S.: Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study. Med. Image Anal. 69:101952 (2021)
2.
Sekuboyina, A.* et al.: VERSE: A Vertebrae labelling and segmentation benchmark for multi-detector CT images. Med. Image Anal. 73:102166 (2021)
3.
Peter, L.* et al.: Assisting the examination of large histopathological slides with adaptive forests. Med. Image Anal. 35, 655-668 (2016)
4.
Pontabry, J. ; Rousseau, F.* ; Studholme, C.* ; Koob, M.* & Dietemann, J.L.*: A discriminative feature selection approach for shape analysis: Application to fetal brain cortical folding. Med. Image Anal. 35, 313-326 (2016)
5.
Eslami, A. ; Karamalis, A.* ; Katouzian, A.* & Navab, N.*: Segmentation by retrieval with guided random walks: Application to left ventricle segmentation in MRI. Med. Image Anal. 17, 236-253 (2013)
6.
Kirişli, H.A.* et al.: Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography. Med. Image Anal. 17, 859-876 (2013)
7.
Vogel, J.* ; Lasser, T. ; Gardiazabal, J.* & Navab, N.*: Trajectory optimization for intra-operative nuclear tomographic imaging. Med. Image Anal. 17, 723-731 (2013)