23 March 2017 Virtual setting for training in interpreting mammography images
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Abstract
This work presents a web system for the training of students or residents (users) interested in the detection of breast density in mammography images. The system consists of a breast imaging database with breast density types classified and demarcated by the specialist (tutor) or online database. The planning was based on ISO / IEC 12207. Through the browser (desktop or notebook), the user will visualize the breast images and in them will realize the markings of the density region and even classify them per the BI-RADS protocol. After marking, this will be compared to the gold standard already existing in the image base, and then the system will inform if the area demarcation has been set or not. The shape of this marking is similar to the paint brush. The evaluation was based on ISO / IEC 1926 or 25010: 2011 by 3 software development specialists and 3 in mammary radiology, evaluating usability, configuration, performance and System interface through the Likert scale-based questionnaire. Where they have totally agreed on usability, configuration, performance and partially on the interface. And as a good thing: the system is able to be accessed anywhere and at any time, the hit or error response is in real time, it can be used in the educational area, the limit of the amount of images will depend on the size of the computer memory, At the end the system sends the results achieved by e-mail to the user, reproduction of the system on any type of screen, complementation of the system with other types of breast structures. Negative points are the need for internet.
Conference Presentation
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J. L. Pezzuol, J. L. Pezzuol, F. D. L. Abreu, F. D. L. Abreu, S. M. Silva, S. M. Silva, A. Tendolini, A. Tendolini, M. A. Se Bissaco, M. A. Se Bissaco, S. C. M. Rodrigues, S. C. M. Rodrigues, } "Virtual setting for training in interpreting mammography images", Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 101380U (23 March 2017); doi: 10.1117/12.2254677; https://doi.org/10.1117/12.2254677
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