K-nearest neighbor is one of the simplest and most intuitive binary classification methods providing robust results on a wide range of data. However, classification results can be improved by using a decision method that is capable of assigning, if necessary, the minority label from the list of neighbors of a tested instance. In this…
INTRODUCTION Prostate magnetic resonance imaging (MRI) has been recently integrated into the pathway of diagnosis of prostate cancer (PCa). However, the lack of an optimal contrast-to-noise ratio hinders automatic recognition of suspicious lesions, thus developing a solution for proper delimitation of the tumour and its separation from the healthy parenchyma, which is of primordial…
Introduction Bladder magnetic resonance imaging (MRI) has been recently integrated in the diagnosis pathway of bladder cancer. However, automatic recognition of suspicious lesions is still challenging. Thus, development of a solution for proper delimitation of the tumor and its separation from the healthy tissue is of primordial importance. As a solution to this unmet…
In the past five years, 7.8 million women were diagnosed with breast cancer. Breast cancer is curable if it is discovered in early stages. Therefore, mammography screening is essential. But, since interpretation can prove difficult, various automated interpretation systems have been proposed so far. A crucial step of the interpretation process is segmentation: identifying…
Combining cellular automata (CA) with convolutional neural networks (CNN) has been overtime an important topic of scientific interest in the field of computer vision. This has been due to the high number of common aspects between the two models, such as extracting information and making decision based on pixel neighbourhoods. While there are many…
Breast cancer is the most frequent type of malignancy in women, with 2.3 million diagnostics only in 2020. However, as a consequence of early diagnosis and appropriate treatment, more and more women are being cured. Among screening methods, mammography is one of the most used, and segmentation is a crucial step of its analysis.…
Brain disorders are becoming more prevalent, and accurate brain segmentation is a vital component of identifying the appropriate treatment. This study introduces an enhanced graph-based image segmentation technique. The node selection process involves creating an ellipsoid centered at the image’s center of mass. The proposed approach is evaluated using the NFBS dataset and demonstrates…
Automating artificial intelligence (AI) model training has emerged as a significant challenge in the field of automation. The complete pipeline from raw data to model deployment poses the need to define robust processes that ensure the efficiency of the services that expose the models. This paper introduces a generic architecture for automating data preparation,…
The field of Artificial Intelligence (AI) has rapidly transformed from a buzzword technology to a fundamental aspect of numerous industrial software applications. However, this quick transition has not allowed for the development of robust best practices for designing and implementing processes related to data engineering, machine learning (ML)-based model training, deployment, monitoring, and maintenance.…
Malicious links are becoming the main propagating vector for web-malware. They may lead to serious security issues, such as phishing, distribution of fake news and low-quality content, drive-by-downloads, and malicious code running. Malware link detection is a challenging domain because of the dynamics of the on-line environment, where web links and web content are…