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Rosado L.,Fraunhofer Portugal AICOS | Vasconcelos M.J.M.,Fraunhofer Portugal AICOS
HEALTHINF 2015 - 8th International Conference on Health Informatics, Proceedings; Part of 8th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015 | Year: 2015

Nowadays, skin cancer is considered one of the most common malignancies in the Caucasian population, thus it is crucial to develop methodologies to prevent it. Because of that, Mobile Teledermatology (MT) is thriving, allowing patients to adopt an active role in their health status while facilitating doctors to early diagnose skin cancers. Skin lesion segmentation is one of the most important and difficult task in computerized image analysis process, and so far the attention is mainly turned to dermoscopic images. In order to turn MT more accurate, it is therefore fundamental to develop simple segmentation methodologies specifically designed for macroscopic images or images acquired via smartphones, which is the main focus of this work. The proposed method was applied in 80 images acquired via smartphones and promising results have been achieved: a mean Jaccard index of 81%, mean True Detection Rate of 96% and mean Accuracy around 98%. The major goal of this work is to develop a mobile application easily accessible for the general population, with the aim of raise awareness and help both patients and doctors in the early diagnosis of skin cancers.

Vasconcelos M.J.M.,Fraunhofer Portugal AICOS | Rosado L.,Fraunhofer Portugal AICOS | Ferreira M.,Portuguese Institute of Oncology
2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 - Proceedings | Year: 2015

The incidence of melanoma has been increasing steadily over the past few decades throughout most of the world. The development of computer diagnosis systems that use dermoscopic images can be of great help for the diagnosis of melanoma. This paper presents an image processing and analysis methodology using supervised classification to independently assess the Asymmetry, Border, Color and Dermoscopic Structures score according to the ABCD rule, and the corresponding Total Dermatoscopy Score of a skin lesion using dermoscopic images. A dermoscopic image dataset was used to test the proposed approach, annotated by dermatology specialists according to the ABCD rule and being the confirmed malignant melanomas also identified. Accuracy rates of 74.0%, 78.3% and 53.5% were achieved for the estimation of the ABCD score of the Asymmetry, Border and Color criterion, as well as accuracy rates for the presence of the five Differential Structures of 72.4%, 68.5%, 74.0%, 74.0% and 85.8% for dots, globules, streaks homogeneous areas and pigment network. Moreover, sensitivity and specificity rates of 93.3% and 69.1% were achieved for the classification of the dermoscopic images as melanoma or non-melanoma. © 2015 IEEE.

Vasconcelos M.J.M.,Fraunhofer Portugal AICOS | Rosado L.,Fraunhofer Portugal AICOS
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

One of the most important challenges of dealing with digital images acquired under uncontrolled conditions is the capability to assess if the image has enough quality to be further analyzed. In this scenario, blur can be considered as one of the most common causes for quality degradation in digital pictures, particularly in images acquired using mobile devices. In this study, we collected a set of 78 features related with blur detection and further analyzed its individual discriminatory ability for two dermatologic image datasets. For the dataset of dermoscopic images with artificially induced blur, high separation levels were obtained for the features calculated using DCT/DFT and Lapacian groups, while for the dataset of mobile acquired images, the best results were obtained for features that used Laplacian and Gradient groups. © 2014 Springer International Publishing.

De Barros A.C.,Fraunhofer Portugal AICOS | Leitao R.,Sheffield Hallam University | Ribeiro J.,Fraunhofer Portugal AICOS
Procedia Computer Science | Year: 2013

Smartphones are becoming increasingly widespread around the globe and are ever more accessible to everyone, including older adults, who are traditionally seen as experiencing difficulties in interacting with information and communication technologies. While these devices are increasingly being used to cover health needs, there are not sufficient studies addressing usability of smartphone user interfaces for older adults. This paper describes the design and evaluation process of the user interface of a smartphone application designed to promote exercise and prevent falls amongst older adults. Iteratively, three successive versions of the user interfaces were tested with different groups of older adults. The results and findings from three rounds of usability tests led to recommendations regarding inclusive design and designing for older adults that may be a useful contribution to the broader community when designing interfaces for smartphones. © 2013 The Authors. Published by Elsevier B.V.

Rosado L.,Fraunhofer Portugal AICOS | Ferreira M.,Portuguese Institute of Oncology of Porto
Proceedings - 2013 2nd Experiment@ International Conference, exp.at 2013 | Year: 2013

Mobile Teledermatology appears nowadays as a promising tool with the potential to empower patients to adopt an active role in managing their own health status, while facilitates the early diagnosis of skin cancers. The main objective of this work is to create a mobile-based prototype to analyze skin lesions based on supervised classification. The presented self-monitoring system collects, processes and storages information of skin lesions through the automatic extraction and classification of specific visual features. The selected features are based on the ABCD rule, which considers 4 visual criteria considered highly relevant for the detection of malignant melanoma. The algorithms used to extract and classify these features are briefly described, as well as the overall system requirements and architecture. © 2013 IEEE.

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