Histology Image Collection Library
Microscopy image analysis of p63 immunohistochemically stained laryngeal cancer lesions for predicting patient 5-year survivalNinos, K., Kostopoulos, S., Kalatzis, I., Sidiropoulos, K., Ravazoula, P., Sakellaropoulos, G., Panayiotakis, G., Economou, G., Cavouras, D. (2016) European Archives of Oto-Rhino-Laryngology, 273 (1), pp. 159-168
Assessing the performance of four different categories of histological criteria in brain tumours grading by means of a computer-aided diagnosis image analysis system Kostopoulos, S., Konstandinou, C., Sidiropoulos, K., Ravazoula, P., Kalatzis, I., Asvestas, P., Cavouras, D., Glotsos, D. (2015) Journal of Microscopy, 260 (1), pp. 37-46.
A GPU-based computer-assisted microscopy system for assessing the importance of different families of histological characteristics in cancer diagnosis Glotsos, D., Kostopoulos, S., Sidiropoulos, K., Ravazoula, P., Kalatzis, I., Asvestas, P., Cavouras, D. (2014) Proceedings of SPIE - The International Society for Optical Engineering, 9069, art. no. 90691I.
Computer based correlation of the texture of P63 expressed nuclei with histological tumour grade, in laryngeal carcinomas Ninos K., Kostopoulos S., Kalatzis I., Ravazoula P., Sakelaropoulos G., Panayiotakis G., Economou G., Cavouras D. (2014) Analytical Cellular Pathology, Article ID 963076.
Computer-based image analysis system designed to differentiate between low-grade and high-grade laryngeal cancer cases Ninos, K., Kostopoulos, S., Sidiropoulos, K., Kalatzis, I., Glotsos, D., Athanasiadis, E., Ravazoula, P., Panayiotakis, G., Economou, G., Cavouras, D. (2013) Analytical and Quantitative Cytology and Histology, 35 (5), pp. 261-272.
Real time decision support system for diagnosis of rare cancers, trained in parallel, on a graphics processing unit Sidiropoulos, K., Glotsos, D., Kostopoulos, S., Ravazoula, P., Kalatzis, I., Cavouras, D., Stonham, J. (2012) Computers in Biology and Medicine, 42 (4), pp. 376-386.
A pilot study investigating the minimum requirements necessary for grading astrocytomas remotely Glotsos, D., Georgiadis, P., Kostopoulos, S., Daskalakis, A., Kalatzis, I., Ravazoula, P., Cavouras, D. (2009) Analytical and Quantitative Cytology and Histology, 31 (5), pp. 262-268.
Computer-based association of the texture of expressed estrogen receptor nuclei with histologic grade using immunohistochemically-stained breast carcinomas Kostopoulos, S., Glotsos, D., Cavouras, D., Daskalakis, A., Kalatzis, I., Georgiadis, P., Bougioukos, P., Ravazoula, P., Nikiforidis, G. (2009) Analytical and Quantitative Cytology and Histology, 31 (4), pp. 187-196.
Cascade pattern recognition structure for improving quantitative assessment of ER-status in breast tissue carcinomasKostopoulos S., Cavouras D., Daskalakis A., Kagadis G.C, Kalatzis I., Georgiadis P., Ravazoula P., Nikiforidis G. (2008) Analytical Quantitative Cytology Histology, 30, pp. 218-225.
Improving accuracy in astrocytomas grading by integrating a robust least squares mapping driven support vector machine classifier into a two level grade classification schemeGlotsos, D., Kalatzis, I., Spyridonos, P., Kostopoulos, S., Daskalakis, A., Athanasiadis, E., Ravazoula, P., Nikiforidis, G., Cavouras, D. (2008) Computer Methods and Programs in Biomedicine, 90 (3), pp. 251-261.
Brain tumor characterization using the soft computing technique of fuzzy cognitive mapsPapageorgiou, E.I., Spyridonos, P.P., Glotsos, D.Th., Stylios, C.D., Ravazoula, P., Nikiforidis, G.N., Groumpos, P.P. (2008) Applied Soft Computing Journal, 8 (1), pp. 820-828.
An image-analysis system based on support vector machines for automatic grade diagnosis of brain-tumour astrocytomas in clinical routineGlotsos, D., Spyridonos, P., Cavouras, D., Ravazoula, P., Arapantoni Dadioti, P., Nikiforidis, G. (2005) Informatics for Health and Social Care, 30 (3), pp. 179-193.
Automated diagnosis of brain tumours astrocytomas using probabilistic neural network clustering and support vector machinesGlotsos, D., Tohka, J., Ravazoula, P., Cavouras, D., Nikiforidis, G. (2005) International Journal of Neural Systems, 15 (1-2), pp. 1-11.
Automated diagnosis of brain tumours using a novel density estimation method for image segmentation and independent component analysis combined with support vector machines for image classificationGlotsos, D., Spyridonos, P., Ravazoula, P., Cavouras, D., Nikiforidis, G. (2004) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3316, pp. 1058-1063.
Automated segmentation of routinely hematoxylin-eosin-stained microscopic images by combining support vector machine clustering and active contour modelsGlotsos, D., Spyridonos, P., Cavouras, D., Ravazoula, P., Dadioti, P.-A., Nikiforidis, G.(2004) Analytical and Quantitative Cytology and Histology, 26 (6), pp. 331-340.
Computer-Based Malignancy Grading of Astrocytomas Employing a Support Vector Machine Classifier, the WHO Grading System and the Regular Hematoxylin-Eosin Diagnostic Staining ProcedureGlotsos, D., Spyridonos, P., Petalas, P., Cavouras, D., Ravazoula, P., Dadioti, P.-A., Lekka, I., Nikiforidis, G. (2004) Analytical and Quantitative Cytology and Histology, 26 (2), pp. 77-83.