iPixel: a visual content-based and semantic search engine for retrieving digitized mammograms by using collective intelligence.

Nowadays, traditional search engines such as Google, Yahoo and Bing facilitate the retrieval of information in the format of images, but the results are not always useful for the users. This is mainly due to two problems: (1) the semantic keywords are not taken into consideration and (2) it is not always possible to establish a query using the image features. This issue has been covered in different domains in order to develop content-based image retrieval (CBIR) systems. The expert community has focussed their attention on the healthcare domain, where a lot of visual information for medical analysis is available. This paper provides a solution called iPixel Visual Search Engine, which involves semantics and content issues in order to search for digitized mammograms. iPixel offers the possibility of retrieving mammogram features using collective intelligence and implementing a CBIR algorithm. Our proposal compares not only features with similar semantic meaning, but also visual features. In this sense, the comparisons are made in different ways: by the number of regions per image, by maximum and minimum size of regions per image and by average intensity level of each region. iPixel Visual Search Engine supports the medical community in differential diagnoses related to the diseases of the breast. The iPixel Visual Search Engine has been validated by experts in the healthcare domain, such as radiologists, in addition to experts in digital image analysis.

ITOHealth: a multimodal middleware-oriented integrated architecture for discovering medical entities.

Emergency healthcare is one of the emerging application domains for information services, which requires highly multimodal information services. The time of consuming pre-hospital emergency process is critical. Therefore, the minimization of required time for providing primary care and consultation to patients is one of the crucial factors when trying to improve the healthcare delivery in emergency situations. In this sense, dynamic location of medical entities is a complex process that needs time and it can be critical when a person requires medical attention. This work presents a multimodal location-based system for locating and assigning medical entities called ITOHealth. ITOHealth provides a multimodal middleware-oriented integrated architecture using a service-oriented architecture in order to provide information of medical entities in mobile devices and web browsers with enriched interfaces providing multimodality support. ITOHealth's multimodality is based on the use of Microsoft Agent Characters, the integration of natural language voice to the characters, and multi-language and multi-characters support providing an advantage for users with visual impairments.