Enhancing Breast Cancer Classification using a Modified GoogLeNet Architecture with Attention Mechanism

Al-Iraqia Journal of Scientific Engineering Research, Год журнала: 2024, Номер 3(1)

Опубликована: Март 1, 2024

Breast cancer incidence has been soaring sharply, and this is causing grave concern worldwide due to its high mortality rates. It should be correctly diagnosed in the early stages order achieve better patient outcomes. Over last decade, there a great demand for diagnosis systems based on AI that could used breast detection classification. These computerized devices utilize deep learning algorithms analyze medical scans thereby allowing subtle abnormality recognition distinguishing malignant from benign tumors. Computer-aided named CAD can assist radiologists pathologists more precise with their diagnoses while at same time increasing productivity. Furthermore, recent advances CNN architectures coupled attention mechanisms have further improved diagnosis. Attention-based models focus crucial regions hence enhancing classification accuracy reliability. In study, we introduce new approach improves of using GoogLeNet architecture modified by an mechanism image regions. The spatial transformer network (STN), which allows it significant areas histopathology images selective attention. Through mechanism, model becomes discriminatory features indicate different subtypes cancer. evaluate effectiveness method, implemented experiments BreaKHis dataset classifying carcinomas. This intentionally collected under various magnifications so as facilitate binary multiple tasks. outcomes clearly show outperforms original terms accuracy. For classification, proposed demonstrated rate 98.08%, whereas GoogLeNet's was 94.99%. multi-class 100x magnification, achieved 94.63% 85.06%. evident these findings efficiency significantly approach. study incorporating framework improve performance. Combining together lead accurate treatment decisions results. More efforts are needed develop area ongoing endeavors towards upgrading them ultimately contribute saving many lives fight against

Язык: Английский

Enhanced Breast Cancer Diagnosis: Leveraging Customized Transfer Learning with Machine Learning and Attention Mechanisms for Histopathology Image Classification

Опубликована: Авг. 8, 2024

Язык: Английский