Tag: mammographic image

Analyzing the Impact of Data Augmentation on Tumor Detection and Classification in Mammograms (2025)

Hybrid Artificial Intelligence Systems Authors Madalina Dicu, Enol García González, Camelia Chira, José R. Villar Abstract Breast cancer remains one of the leading causes of mortality among women worldwide, making early detection crucial for improving survival rates. Deep learning-based approaches have shown remarkable potential in automating tumor detection from mammographic images; however, their effectiveness…

Preprocessing Techniques for Optimizing Mammograms Segmentation: a Cellular Automaton Approach (2025)

Procedia Computer Science Authors Iulia-Andreea Ion, Cristiana Moroz-Dubenco, A. Andreica Abstract Breast cancer is the most commonly diagnosed cancer among women worldwide, with early detection playing an essential role in improving survival rates. Detection of breast abnormalities at an early stage is best performed using mammography. This paper presents a new approach integrating advanced…

Significance of Training Images and Feature Extraction in Lesion Classification (2024)

International Conference on Agents and Artificial Intelligence Authors Adél Bajcsi, A. Andreica, C. Chira Abstract Proper treatment of breast cancer is essential to increase survival rates. Mammography is a widely used, non-invasive screening method for breast cancer. A challenging task in mammogram analysis is to distinguish between tumors. In the current study, we address…

Generalizing an Improved GrowCut Algorithm for Mammography Lesion Detection (2023)

Hybrid Artificial Intelligence Systems Authors Cristiana Moroz-Dubenco, L. Dioşan, A. Andreica Abstract 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…

Towards an Unsupervised GrowCut Algorithm for Mammography Segmentation (2023)

International Conference on Virtual Storytelling Authors Cristiana Moroz-Dubenco, L. Dioşan, A. Andreica Abstract 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…

Breast Cancer Images Segmentation using Fuzzy Cellular Automaton (2023)

International Conference on Knowledge-Based Intelligent Information & Engineering Systems Authors Iulia-Andreea Ion, Cristiana Moroz-Dubenco, A. Andreica Abstract Breast cancer is the most common type of cancer found in women. One of the most effiective methods for early identification of breast cancer is the mammogram. Numerous computer-aided systems for detecting breast cancer from mammograms have…

Linear Discriminant Analysis Tumour Classification for Unsupervised Segmented Mammographies (2023)

International Conference on Knowledge-Based Intelligent Information & Engineering Systems Authors Cristiana Moroz-Dubenco, A. Andreica Abstract Between 2015 and 2020, 7.8 million women were diagnosed with breast cancer. If the cancer is discovered early, it can be completely cured. Computer-aided detection and diagnosis systems are a helpful tool. We propose such a system: after pre-processing…

Extended Mammogram Classification From Textural Features (2023)

Studia Universitatis Babeș-Bolyai Informatica Authors Adél Bajcsi, C. Chira, A. Andreica Abstract The efficient analysis of digital mammograms has an important role in the early detection of breast cancer and can lead to a higher percentage of recovery. This paper presents an extended computer-aided diagnosis system for the classification of mammograms into three classes…

The Impact of Convolutional Neural Network Parameters in the Binary Classification of Mammograms (2022)

Symposium on Symbolic and Numeric Algorithms for Scientific Computing Authors Madalina Dicu, L. Dioşan, A. Andreica, C. Chira, Alin Cordoş Abstract Breast cancer is the most commonly diagnosed type of cancer. It is essential to classify patients as quickly as possible into groups with a high or low risk of cancer, to provide adequate…