Presentation of Novel Hybrid Algorithm for Detection and Classification of Breast Cancer Using Growth Region Method and Probabilistic Neural Network

Abstract

Mammography is a significant screening test for early detection of breast cancer, which increases the patient’s chances of complete recovery. In this paper, a clustering method is presented for the detection of breast cancer tumor locations and areas. To implement the clustering method, we used the growth region approach. This method detects similar pixels nearby. To find the best initial point for detection, it is essential to remove human interaction in clustering. Therefore, in this paper, the FCM-GA algorithm is used to find the best point for starting growth. Their results are compared with the manual selection method and Gaussian Mixture Model method for verification. The classification is performed to diagnose breast cancer type in two primary datasets of MIAS and BI-RADS using features of GLCM and probabilistic neural network (PNN). Results of clustering show that the presented FCM-GA method outperforms other methods. Moreover, the accuracy of the clustering method for FCM-GA is 94%, as the best approach used in this paper. Furthermore, the result shows that the PNN methods have high accuracy and sensitivity with the MIAS dataset.

Awakening Effect of Transcranial Magnetic Stimulation with Multimodal Magnetic Resonance Imaging under Three-Dimensional Reconstruction Algorithm Combined with Wake-Up Nursing on Patients with Massive Cerebral Infarction

“…e second was to remove skull in the image. When the MRI skull was segmented, the more commonly used algorithm was the region growing algorithm, but this method was limited by the unclear border between the skull and brain tissues [21]. erefore, a method combining automatic thresholding and boundary tracking was put forward.…”

A Newly Hybrid Version of African Vultures Optimization Algorithm and Sine Cosine Algorithm for Mammographic Masses and its Diagnosis

“…Where, L 1 and L 2 denotes the values b/w 0 and 1 (sum=1).The superior values have been attained with Roulette wheel by formula (7) as follows.…”

“…al. [7] presented a hybrid technique FCM-GA to get an initial point for detection of abnormality in the mammogram image and then on the basis of similarity of the nearby pixels the starting point is grown to get the whole abnormal part. Intensity and GLCM features are detected of the region obtained previously and then it is classified as malignant or benign using the probabilistic neural network.…”

“…For assessing the hunting behaviour of the AVSC method has been considered unimodal functions which involve a single optima value. Tabulated results of optimizers on these functions have been reported by tables (5)(6)(7)(8)(9)(10). Attained solutions reveal that the AVSC method is able to trap the best optima value in the complex domain with least number of iterations than others.…”

Reduced hardware requirements of deep neural network for breast cancer diagnosis

“…Mammography is the traditional way for early detection of breast cancer, which increases the patient's chance to beat cancer [1]. Another way is to use computerized methods under two conditions: correctly and timely.…”