Artificial neural networks applications in computer aided diagnosis
Jorge Hernández‐Rodríguez, María José Rodríguez Conde, Francisco Javier Cabrero Fraile · 2016
This paper describes the motivation, state-of-the-art, hypotheses and research objectives of the Doctoral Thesis "Artificial Neural Networks applications in Computer Aided Diagnosis. System design and use as an educational tool". A description of the investigation approaches and methodologies, the current dissertation status and expected contributions is also presented. At the time of writing, this dissertation is in its first year of development. Its central topic is Computer Aided Diagnosis and Detection (CAD), a valuable automated tool for specialists who interpret medical images, that provides information which can be used as a "second opinion" or supplementary data in their decision making process. Developing CAD schemes based in the machine learning models called Artificial Neural Networks (ANNs), which could be applied to different image modalities, is the main objective of the first phase of the dissertation. Their integration in a software environment that allows the user to handle and access to information efficiently is of key importance in the process. The validation of the system in clinical practice and the investigation of their possible uses as an educational tool for trainees during residency programs is the second phase.