Medical image recognition is one of the most important unsolved problems in medicine. Taking the mammogram as the object for research, this paper proposes a method for mammographic image recognition using rough sets and support vector machines (SVMs). Firstly, reduce mammographic noise. Secondly, extract texture and shape features to consist of feature vector that can represent the mammogram ac...

Previous works on breast tissue identification and abnormalities detection notice that the feature extraction process is affected if the region processed is not well focused. Thereby, it is important to split the mammogram into interesting regions to achieve optimal breast parenchyma measurements, breast registration or to put into focus a technique when we search for abnormalities. In this pap...

Extraction of the breast border and simultaneously exclusion of pectoral muscle are principal steps for diagnosing of breast cancer based on mammogram data. The objective of propose method is to classify the mediolateral oblique fragment of the pectoral muscle. The extraction of breast region is performed using the multilevel wavelet decomposition of mammogram images. Moreover, artifact suppres...

Sponsored by 2 Tomosynthesis enables definitive identification of unsuspected lesions in multifocal or multicentric cancers, decreasing the need for second-look US and post-MRI biopsy 4 Tomosynthesis finds a spiculated mass not seen in traditional 2D mammogram 6 Tomosynthesis significantly reduces screening callback rates and increases our ability to detect early cancers 8 Diagnosis of US/MRI-o...

Penyakit kanker payudara saat ini menjadi salah satu penyakit mematikan dan umumnya terjadi pada wanita. Kanker dapat dideteksi dengan menggunakan alat mammografi. Citra mammogram memiliki beberapa tipe abnormalitas yang bentuknya seperti noda kecil terdapat titik-titik, dimana massa didalamnya, Massa karakteristik berbeda dalam hal bentuk, batas tepi densitas digunakan menentukan pengklasifika...

Breast cancer is one of the deadliest cancers in world. It essential to detect signs as early possible, make survival rate higher. However, detecting breast using machine or deep learning algorithms from diagnostic imaging results not trivial. Slight changes illumination scanned area can significantly affect automatic classification process. Hence, research aims propose an classifier for digita...