ΈρευναΙατρική απεικόνιση & υπολογιστική όραση

Ανάλυση Δερμοσκοπικής Εικόνας

Υπολογιστική όραση που μετατρέπει τις δερμοσκοπικές εικόνες σε αντικειμενικές μετρήσεις για την έγκαιρη διάγνωση του μελανώματος.

Ανάλυση Δερμοσκοπικής Εικόνας

Η δερμοσκόπηση μεγεθύνει τις μελαγχρωματικές βλάβες του δέρματος και αναδεικνύει δομές που δεν είναι ορατές με γυμνό μάτι. Αναπτύσσουμε μεθόδους υπολογιστικής όρασης που μετατρέπουν αυτές τις εικόνες σε αντικειμενικές και επαναλήψιμες μετρήσεις, υποστηρίζοντας την έγκαιρη διάγνωση του μελανώματος.

Η έρευνά μας καλύπτει ολόκληρη την αλυσίδα επεξεργασίας: αφαίρεση τριχών και θορύβου, κατάτμηση της βλάβης και ανίχνευση του ορίου της, εξαγωγή χαρακτηριστικών χρώματος, υφής και δομών, όπως σφαιρίδια και κουκκίδες, και ταξινόμηση με κλασική μηχανική μάθηση και βαθιά νευρωνικά δίκτυα.

  • Αφαίρεση τριχών και θορύβου
  • Κατάτμηση και ανάλυση ορίων βλάβης
  • Ταξινόμηση με χαρακτηριστικά και βαθιά μάθηση

Σχετικές δημοσιεύσεις

Επιλεγμένες εργασίες του εργαστηρίου σε αυτό το πεδίο.

2025

Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review

Kallipolitis, A., Moutselos, K., Zafeiriou, A., Andreadis, S., Matonaki, A., Stavropoulos, T.G. and Maglogiannis, I. (2025)

BMC Medical Informatics and Decision Making, 25(1).

DOI

2025

Vitiligo Skin Segmentation: An Image-Based Unsupervised Learning Approach

Tziomaka, M., Kallipolitis, A., Andreadis, S., Matonaki, A., Stavropoulos, T.G. and Maglogiannis, I. (2025)

In Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024). Springer Nature Singapore, pp. 246–255.

DOI

2023

Automated hair removal in dermoscopy images using shallow and deep learning neural architectures

Delibasis, K., Moutselos, K., Vorgiazidou, E. and Maglogiannis, I. (2023)

Computer Methods and Programs in Biomedicine Update, 4, p. 100109.

DOI

2022

On the Reusability of ISIC Data for Training DL Classifiers Applied on Clinical Skin Images

Moutselos, K. and Maglogiannis, I. (2022)

In Artificial Intelligence Applications and Innovations. AIAI 2022 IFIP WG 12.5 International Workshops. Springer International Publishing, pp. 199–212.

DOI

2021

Ensembles of Deep Convolutional Neural Networks for Detecting Melanoma in Dermoscopy Images

Tziomaka, M. and Maglogiannis, I. (2021)

In Computational Collective Intelligence. Springer International Publishing, pp. 523–535.

DOI

2020

Fully Connected Visual Words for the Classification of Skin Cancer Confocal Images

Kallipolitis, A. and Maglogiannis, I. (2020)

In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS – Science and Technology Publications, pp. 853–858.

DOI

2020

Explainable Fully Connected Visual Words for the Classification of Skin Cancer Confocal Images

Kallipolitis, A., Stratigos, A., Zarras, A. and Maglogiannis, I. (2020)

In 11th Hellenic Conference on Artificial Intelligence. ACM, pp. 67–73.

DOI

2020

A Review on State-of-the-Art Computer-Based Approaches for the Early Recognition of Malignant Melanoma

Kontogianni, G. and Maglogiannis, I. (2020)

In Advanced Computational Intelligence in Healthcare-7. Springer Berlin Heidelberg, pp. 81–101.

DOI

2018

Improving the performance of convolutional neural network for skin image classification using the response of image analysis filters

Georgakopoulos, S.V., Kottari, K., Delibasis, K., Plagianakos, V.P. and Maglogiannis, I. (2018)

Neural Computing and Applications, 31(6), pp. 1805–1822.

DOI

2017

Detection of Malignant Melanomas in Dermoscopic Images Using Convolutional Neural Network with Transfer Learning

Georgakopoulos, S.V., Kottari, K., Delibasis, K., Plagianakos, V.P. and Maglogiannis, I. (2017)

In Engineering Applications of Neural Networks. Springer International Publishing, pp. 404–414.

DOI

2015

Hair removal on dermoscopy images

Maglogiannis, I. and Delibasis, K. (2015)

In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, pp. 2960–2963.

DOI

2015

Automated Detection of Streaks in Dermoscopy Images

Delibasis, K., Kottari, K. and Maglogiannis, I. (2015)

In Artificial Intelligence Applications and Innovations. Springer International Publishing, pp. 45–60.

DOI

2014

Skin Lesions Image Analysis Utilizing Smartphones and Cloud Platforms

Doukas, C., Stagkopoulos, P. and Maglogiannis, I. (2014)

In Mobile Health Technologies. Springer New York, pp. 435–458.

DOI

2015

Enhancing classification accuracy utilizing globules and dots features in digital dermoscopy

Maglogiannis, I. and Delibasis, K.K. (2015)

Computer Methods and Programs in Biomedicine, 118(2), pp. 124–133.

DOI

2012

Automated skin lesion assessment using mobile technologies and cloud platforms

Doukas, C., Stagkopoulos, P., Kiranoudis, C.T. and Maglogiannis, I. (2012)

In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, pp. 2444–2447.

DOI

2011

Independent Component Clustering for Skin Lesions Characterization

Tasoulis, S.K., Doukas, C.N., Maglogiannis, I. and Plagianakos, V.P. (2011)

In Artificial Intelligence Applications and Innovations. Springer Berlin Heidelberg, pp. 472–482.

DOI

2011

A medical ontology for intelligent web-based skin lesions image retrieval

Maragoudakis, M. and Maglogiannis, I. (2011)

Health Informatics Journal, 17(2), pp. 140–157.

DOI

2010

Skin lesion diagnosis from images using novel ensemble classification techniques

Maragoudakis, M. and Maglogiannis, I. (2010)

In Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine. IEEE, pp. 1–5.

DOI

2010

Classification of dermatological images using advanced clustering techniques

Tasoulis, S.K., Doukas, C.N., Maglogiannis, I. and Plagianakos, V.P. (2010)

In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology. IEEE, pp. 6721–6724.

DOI

2010

Skin Lesions Characterisation Utilising Clustering Algorithms

Tasoulis, S.K., Doukas, C.N., Maglogiannis, I. and Plagianakos, V.P. (2010)

In Artificial Intelligence: Theories, Models and Applications. Springer Berlin Heidelberg, pp. 243–253.

DOI

2009

Overview of Advanced Computer Vision Systems for Skin Lesions Characterization

Maglogiannis, I. and Doukas, C.N. (2009)

IEEE Transactions on Information Technology in Biomedicine, 13(5), pp. 721–733.

DOI

2007

Reviewing State of the Art AI Systems for Skin Cancer Diagnosis

Maglogiannis, I. and Doukas, C. (2007)

In Maglogiannis, I., Karpouzis, K., Wallace, M. and Soldatos, J. (eds) Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies. Frontiers in Artificial Intelligence and Applications, 160. Amsterdam: IOS Press.

2007

Skin Lesion Recognition with Region Growing Methods

Maglogiannis, I. (2007)

In Zharkova, V.V. and Jain, L.C. (eds) Intelligent Paradigms of Feature Recognition in Astrophysical and Medical Images. Berlin: Springer, pp. 123–149.

2007

Detection of Irregular Edges in Skin Lesions Using Parametric Active Contours for Dermatological Digital Images

Maglogiannis, I. (2007)

Journal on Information Technology in Healthcare, 5(2), pp. 97–104.

2006

Computational vision systems for the detection of malignant melanoma

Maglogiannis, I. and Kosmopoulos, D. (2006)

Oncology Reports.

DOI

2005

An Integrated Computer Supported Acquisition, Handling, and Characterization System for Pigmented Skin Lesions in Dermatological Images

Maglogiannis, I., Pavlopoulos, S. and Koutsouris, D. (2005)

IEEE Transactions on Information Technology in Biomedicine, 9(1), pp. 86–98.

DOI

2004

Design and Implementation of a Calibrated Store and Forward Imaging System for Teledermatology

Maglogiannis, I. (2004)

Journal of Medical Systems, 28(5), pp. 455–467.

DOI

2003

Automated Segmentation and Registration of Dermatological Images

Maglogiannis, I. (2003)

Journal of Mathematical Modelling and Algorithms, 2(3), pp. 277–294.

DOI

2003

A system for the acquisition of reproducible digital skin lesions images

Maglogiannis, I. and Kosmopoulos, D.I. (2003)

Technology and Health Care, 11(6), pp. 425–441.

DOI

2026

An Inspectable Vision-Language and Convolutional Ensemble for Facial Pigmented Lesion Diagnosis

Zafeiriou, A., Kallipolitis, A., Tziomaka, M. and Maglogiannis, I. (2026)

In Innovating Bioengineering Through Next-Generation Computational Approaches. Springer Nature Switzerland, pp. 295–312.

DOI

2026

Zero-Shot Segmentation of Skin Conditions: Erythema with Edit-Friendly Inversion

Moutselos, K. and Maglogiannis, I. (2026)

In Proceedings of 2025 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2025). Springer Nature Singapore, pp. 115–125.

DOI

2025

Advanced Multi-class Wound Segmentation Using EfficientNet UNet

Kallipolitis, A., Tziomaka, M., Zafeiriou, A. and Maglogiannis, I. (2025)

In Joint 20th Nordic-Baltic Conference on Biomedical Engineering & 24th Polish Conference on Biocybernetics and Biomedical Engineering. Springer Nature Switzerland, pp. 423–440.

DOI
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