Ioannis Andreadis wins the best student paper award at BIBE 2013

Ioannis Andreadis, member of the Biomedical Simulations and Imaging Laboratory of the NTUA (BIOSIM-NTUA), was the recipient of the Best Student Paper Award in the 13th IEEE Conference on Bioinformatics and Bioengineering (BIBE 2013), held in Chania, Greece, on 10th November 2013. The specific conference covers a broad spectrum of up-to-date topics of Bioinformatics and Bioengineering by giving the opportunity to scientists to participate in the research challenges and opportunities that these two scientific fields bring to modern science.

Mr Ioannis Andreadis’ paper entitled “Variations on breast density and subtlety of the findings require different computational intelligence pipelines for the diagnosis of clustered microcalcifications” was distinguished between nearly 250 papers. The specific paper addresses a major issue concerning the Computer-Aided Diagnosis (CAD) of breast cancer. Breast cancer is one of the most common types of cancer presented among women and one of the leading causes of death worldwide. Towards the early diagnosis of the disease, the analysis of breast microcalcifications is considered a prerequisite step, since their presence is associated to the existence of breast cancer. The subtle nature of these findings makes their interpretation a difficult task, even for experienced radiologists.

Through the specific research work, the authors form the proper baseline to develop consistent and robust methodologies that may support the diagnostic process. Specifically, novel methodologies are implemented for the automated analysis of microcalcifications and evaluated using a dataset of cases that were extracted from public databases, containing mammograms of real-life cases. A subset of almost 1750 different cases have been used, which consists the largest subset of images that has been used in corresponding studies concerning the CAD diagnosis of clusters of MCs. The results of this work are quite promising and it is expected to deduce significant contribution for the clinical assessment of patients with breast microcalcifications.

Concluding, the research work addressed the major challenge of analyzing breast microcalcifications, by ‘projecting’ it to an engineering challenge, consisting in developing novel methodologies for image analysis and incorporating them into a CAD system. Given the encouraging results, this research work is expected to contribute to the improvement of the current diagnostic process, with major benefits for public health.