nach oben

Erschienen in:

2017 | OriginalPaper | Buchkapitel

An Annotation Tool for a Digital Library System of Epidermal Data

verfasst von : Fabrizio Balducci, Guido Borghi

Erschienen in: Digital Libraries and Archives

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Melanoma is one of the deadliest form of skin cancers so it becomes crucial the developing of automated systems that analyze and investigate epidermal images to early identify them also reducing unnecessary medical exams. A key element is the availability of user-friendly annotation tools that can be used by non-IT experts to produce well-annotated and high-quality medical data. In this work, we present an annotation tool to manually crate and annotate digital epidermal images, with the aim to extract meta-data (annotations, contour patterns and intersections, color information) stored and organized in an integrated digital library. This tool is obtained following rigid usability principles also based on doctors interviews and opinions. A preliminary but functional evaluation phase has been conducted with non-medical subjects by using questionnaires, in order to check the general usability and the efficacy of the proposed tool.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Language Identification as Process Prediction Using WoMan

Nächstes Kapitel The Use of Hashtags in the Promotion of Art Exhibitions

Ahlberg, C., Williamson, C., Shneiderman, B.: Dynamic queries for information exploration: an implementation and evaluation. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI 1992, pp. 619–626. ACM, New York (1992). http://doi.acm.org/10.1145/142750.143054

Ali, A.R.A., Deserno, T.M.: A systematic review of automated melanoma detection in dermatoscopic images and its ground truth data. In: SPIE Medical Imaging, p. 83181I. International Society for Optics and Photonics (2012)

Baraldi, L., Grana, C., Cucchiara, R.: Hierarchical boundary-aware neural encoder for video captioning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017)

Baraldi, L., Grana, C., Cucchiara, R.: Recognizing and presenting the storytelling video structure with deep multimodal networks. IEEE Trans. Multimedia 19(5), 955–968 (2017)CrossRef

Barata, C., Ruela, M., Francisco, M., Mendonça, T., Marques, J.S.: Two systems for the detection of melanomas in dermoscopy images using texture and color features. IEEE Syst. J. 8(3), 965–979 (2014)CrossRef

Binder, M., Steiner, A., Schwarz, M., Knollmayer, S., Wolff, K., Pehamberger, H.: Application of an artificial neural network in epiluminescence microscopy pattern analysis of pigmented skin lesions: a pilot study. Br. J. Dermatol. 130(4), 460–465 (1994)CrossRef

Celebi, M.E., Wen, Q., Iyatomi, H., Shimizu, K., Zhou, H., Schaefer, G.: A state-of-the-art survey on lesion border detection in dermoscopy images. In: Dermoscopy Image Analysis, pp. 97–129. CRC Press (2015)

Codella, N., Cai, J., Abedini, M., Garnavi, R., Halpern, A., Smith, J.R.: Deep learning, sparse coding, and svm for melanoma recognition in dermoscopy images. In: Zhou, L., Wang, L., Wang, Q., Shi, Y. (eds.) MLMI 2015. LNCS, vol. 9352, pp. 118–126. Springer, Cham (2015). doi:10.1007/978-3-319-24888-2_15 CrossRef

Codella, N.C.F., Nguyen, Q., Pankanti, S., Gutman, D., Helba, B., Halpern, A., Smith, J.R.: Deep learning ensembles for melanoma recognition in dermoscopy images. CoRR abs/1610.04662 (2016). http://arxiv.org/abs/1610.04662

10.

Corbelli, A., Baraldi, L., Balducci, F., Grana, C., Cucchiara, R.: Layout analysis and content classification in digitized books. In: Agosti, M., Bertini, M., Ferilli, S., Marinai, S., Orio, N. (eds.) IRCDL 2016. CCIS, vol. 701, pp. 153–165. Springer, Cham (2017). doi:10.1007/978-3-319-56300-8_14 CrossRef

11.

Diepgen, T., Mahler, V.: The epidemiology of skin cancer. Br. J. Dermatol. 146(s61), 1–6 (2002)CrossRef

12.

Ercal, F., Chawla, A., Stoecker, W.V., Lee, H.C., Moss, R.H.: Neural network diagnosis of malignant melanoma from color images. IEEE Trans. Biomed. Eng. 41(9), 837–845 (1994)CrossRef

13.

Gibson, J.J., Shaw, R.: Perceiving, acting, and knowing: toward an ecological psychology. The Theory of Affordances, pp. 67–82 (1977)

14.

Grana, C., Baraldi, L., Bolelli, F.: Optimized connected components labeling with pixel prediction. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2016. LNCS, vol. 10016, pp. 431–440. Springer, Cham (2016). doi:10.1007/978-3-319-48680-2_38 CrossRef

15.

Grana, C., Bolelli, F., Baraldi, L., Vezzani, R.: Yacclab-yet another connected components labeling benchmark. In: 2016 23rd International Conference on Pattern Recognition (ICPR), pp. 3109–3114. IEEE (2016)

16.

Gutman, D., Codella, N.C., Celebi, E., Helba, B., Marchetti, M., Mishra, N., Halpern, A.: Skin lesion analysis toward melanoma detection: A challenge at the international symposium on biomedical imaging (isbi) 2016, hosted by the international skin imaging collaboration (isic). arXiv preprint arXiv:1605.01397 (2016)

17.

He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. arXiv preprint arXiv:1512.03385 (2015)

18.

Jaleel, J.A., Salim, S., Aswin, R.: Artificial neural network based detection of skin cancer. IJAREEIE 1, 200–205 (2012)

19.

Kittler, H., Pehamberger, H., Wolff, K., Binder, M.: Diagnostic accuracy of dermoscopy. Lancet Oncol. 3(3), 159–165 (2002)CrossRef

20.

Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in neural Information Processing Systems, pp. 1097–1105 (2012)

21.

Lee, T., Ng, V., Gallagher, R., Coldman, A., McLean, D.: Dullrazor: a software approach to hair removal from images. Comput. Biol. Med. 27(6), 533–543 (1997)CrossRef

22.

Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431–3440 (2015)

23.

Lund, A.M.: Measuring usability with the use questionnaire. Usability Interface 8(2), 3–6 (2001)

24.

Maglogiannis, I., Doukas, C.N.: Overview of advanced computer vision systems for skin lesions characterization. IEEE Trans. Inf Technol. Biomed. 13(5), 721–733 (2009)CrossRef

25.

Marín, C., Alférez, G.H., Córdova, J., González, V.: Detection of melanoma through image recognition and artificial neural networks. In: Jaffray, D.A. (ed.) World Congress on Medical Physics and Biomedical Engineering, June 7-12, 2015, Toronto, Canada. IP, vol. 51, pp. 832–835. Springer, Cham (2015). doi:10.1007/978-3-319-19387-8_204 CrossRef

26.

Mendonça, T., Ferreira, P.M., Marques, J.S., Marcal, A.R., Rozeira, J.: Ph 2-a dermoscopic image database for research and benchmarking. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5437–5440. IEEE (2013)

27.

Norman, D.A.: Affordance, conventions, and design. Interactions 6(3), 38–43 (1999)CrossRef

28.

Pellacani, G., Grana, C., Seidenari, S.: Comparison between computer elaboration and clinical assessment of asymmetry and border cut-off in melanoma images. Exp. Dermatol. 11(6), 609–609 (2002)

29.

Rastgoo, M., Morel, O., Marzani, F., Garcia, R.: Ensemble approach for differentiation of malignant melanoma. In: The International Conference on Quality Control by Artificial Vision 2015, p. 953415. International Society for Optics and Photonics (2015)

30.

Schaefer, G., Krawczyk, B., Celebi, M.E., Iyatomi, H.: An ensemble classification approach for melanoma diagnosis. Memetic Comput. 6(4), 233–240 (2014)CrossRef

31.

Shneiderman, B.: 1.1 direct manipulation: a step beyond programming languages. Sparks of innovation in human-computer interaction 17, 1993 (1993)

32.

Shneiderman, B.: Designing the user interface: strategies for effective human-computer interaction. Pearson Education India (2010)

33.

Singh, S., Stevenson, J., McGurty, D.: An evaluation of polaroid photographic imaging for cutaneous-lesion referrals to an outpatient clinic: a pilot study. Br. J. Plast. Surg. 54(2), 140–143 (2001)CrossRef

34.

Zagrouba, E., Barhoumi, W.: A prelimary approach for the automated recognition of malignant melanoma. Image Anal. Stereol. 23(2), 121–135 (2011)CrossRefMATH

Titel: An Annotation Tool for a Digital Library System of Epidermal Data
verfasst von: Fabrizio Balducci
Guido Borghi
Verlag: Springer International Publishing
Buch: Digital Libraries and Archives
Print ISBN: 978-3-319-68129-0

Electronic ISBN: 978-3-319-68130-6

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-68130-6_14

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"