کنفرانس مهندسی برق ایران

صفحه اصلی / بیست و نهمین کنفرانس مهندسی برق ایران

Noninvasive Diagnosis of the Type of Breast Tumor through Artificial Neural Networks

نویسندگان :

Pooya Tahmasebi¹ Maryam Mehdizadeh Dastjerdi² Ali Fallah³ Saeid Rashidi⁴

1- دانشگاه صنعتی امیرکبیر 2- دانشگاه صنعتی امیرکبیر 3- دانشگاه صنعتی امیرکبیر 4- دانشگاه آزاد اسلامی واحد علوم و تحقیقات بوشهر

کلمات کلیدی :

Breast, Cancer diagnosis, Hyperelastic model, Neural network, Parameter estimation, Tissue modeling

چکیده :

Different changes such as developing benign and malignant lesions in tissues lead to specific variations in their macroscopic and microscopic structure, which are associated with the alteration of their mechanical properties. In the present study, the mechanical parameters of different breast tissue lesions were noninvasively estimated with high precision based on the displacement data by using the powerful neural network method in order to detect the type of tumor in the breast tissue. The displacement data of various breast tissues, as well as the corresponding mechanical properties were acquired to develop and train the neural network models. The finite element modeling using Abaqus software was applied for simulating breast tissue behavior and extracting the relevant displacement data to train the neural networks. Ogden and Yeoh hyperelastic models which are precise for expressing the hyperelastic behavior of soft tissues, specifically the breast, were used to create the finite element model for tumor-containing breast tissue. In order to obtain a robust neural network model, white noise was added into the displacement data extracted from the finite element model to simulate laboratory conditions during deriving tissue data from finite element model. Based on the results, the trained neural network models represent high precision and efficiency in estimating the mechanical parameters of various breast tissues based on the displacement data, which promises its use for carefully diagnosing the type of breast lesion.