Glotsos D - Search Results

1

GPU-enabled design of an adaptable pattern recognition system for discriminating squamous intraepithelial lesions of the cervix.

Konstandinou C, Kostopoulos S, Glotsos D, Pappa D, Ravazoula P, Michail G, Kalatzis I, Asvestas P, Lavdas E, Cavouras D, Sakellaropoulos G. Konstandinou C, et al. Among authors: glotsos d. Biomed Tech (Berl). 2020 May 26;65(3):315-325. doi: 10.1515/bmt-2019-0040. Biomed Tech (Berl). 2020. PMID: 31747374

2

Computer-based malignancy grading of astrocytomas employing a support vector machine classifier, the WHO grading system and the regular hematoxylin-eosin diagnostic staining procedure.

Glotsos D, Spyridonos P, Petalas P, Cavouras D, Ravazoula P, Dadioti PA, Lekka I, Nikiforidis G. Glotsos D, et al. Anal Quant Cytol Histol. 2004 Apr;26(2):77-83. Anal Quant Cytol Histol. 2004. PMID: 15131894

3

Automated segmentation of routinely hematoxylin-eosin-stained microscopic images by combining support vector machine clustering and active contour models.

Glotsos D, Spyridonos P, Cavouras D, Ravazoula P, Dadioti PA, Nikiforidis G. Glotsos D, et al. Anal Quant Cytol Histol. 2004 Dec;26(6):331-40. Anal Quant Cytol Histol. 2004. PMID: 15678615

4

Automated diagnosis of brain tumours astrocytomas using probabilistic neural network clustering and support vector machines.

Glotsos D, Tohka J, Ravazoula P, Cavouras D, Nikiforidis G. Glotsos D, et al. Int J Neural Syst. 2005 Feb-Apr;15(1-2):1-11. doi: 10.1142/S0129065705000013. Int J Neural Syst. 2005. PMID: 15912578

5

An image-analysis system based on support vector machines for automatic grade diagnosis of brain-tumour astrocytomas in clinical routine.

Glotsos D, Spyridonos P, Cavouras D, Ravazoula P, Dadioti PA, Nikiforidis G. Glotsos D, et al. Med Inform Internet Med. 2005 Sep;30(3):179-93. doi: 10.1080/14639230500077444. Med Inform Internet Med. 2005. PMID: 16403707

6

Identifying Differences in the P600 Component of ERP-Signals between OCD Patients and Controls Employing a PNN-based Majority Vote Classification Scheme.

Kalatzis I, Piliouras N, Glotsos D, Ventouras E, Papageorgiou C, Rabavilas A, Soldatos C, Cavouras D. Kalatzis I, et al. Among authors: glotsos d. Conf Proc IEEE Eng Med Biol Soc. 2005;2005:3994-7. doi: 10.1109/IEMBS.2005.1615337. Conf Proc IEEE Eng Med Biol Soc. 2005. PMID: 17281107

7

Improving gene quantification by adjustable spot-image restoration.

Daskalakis A, Cavouras D, Bougioukos P, Kostopoulos S, Glotsos D, Kalatzis I, Kagadis GC, Argyropoulos C, Nikiforidis G. Daskalakis A, et al. Among authors: glotsos d. Bioinformatics. 2007 Sep 1;23(17):2265-72. doi: 10.1093/bioinformatics/btm337. Epub 2007 Jun 28. Bioinformatics. 2007. PMID: 17599935

8

Design of a multi-classifier system for discriminating benign from malignant thyroid nodules using routinely H&E-stained cytological images.

Daskalakis A, Kostopoulos S, Spyridonos P, Glotsos D, Ravazoula P, Kardari M, Kalatzis I, Cavouras D, Nikiforidis G. Daskalakis A, et al. Among authors: glotsos d. Comput Biol Med. 2008 Feb;38(2):196-203. doi: 10.1016/j.compbiomed.2007.09.005. Epub 2007 Nov 9. Comput Biol Med. 2008. PMID: 17996861

9

Improving accuracy in astrocytomas grading by integrating a robust least squares mapping driven support vector machine classifier into a two level grade classification scheme.

Glotsos D, Kalatzis I, Spyridonos P, Kostopoulos S, Daskalakis A, Athanasiadis E, Ravazoula P, Nikiforidis G, Cavouras D. Glotsos D, et al. Comput Methods Programs Biomed. 2008 Jun;90(3):251-61. doi: 10.1016/j.cmpb.2008.01.006. Epub 2008 Mar 17. Comput Methods Programs Biomed. 2008. PMID: 18343526

10

Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods.

Georgiadis P, Cavouras D, Kalatzis I, Glotsos D, Athanasiadis E, Kostopoulos S, Sifaki K, Malamas M, Nikiforidis G, Solomou E. Georgiadis P, et al. Among authors: glotsos d. Magn Reson Imaging. 2009 Jan;27(1):120-30. doi: 10.1016/j.mri.2008.05.017. Epub 2008 Jul 7. Magn Reson Imaging. 2009. PMID: 18602785

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