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The presence of density part of breast tissues is one of the signs considered by radiologists to determine whether a suspicious area is a tumor or cancer. The focus of this research is for the segmentation of dense area with regards to the breast anatomical structure for visualization, such as location of nipple if possible, skin-air interface, fatty tissue, glandular tissue and pectoral muscle. In...
In this paper, the automatic segmentation of Osteosar-coma in MRI images is formed as a clustering problem. Subsequently, a new dynamic clustering algorithm based on the Harmony Search (HS) hybridized with Fuzzy C-means (FCM) called DCHS is proposed to automatically segment the Osteosarcoma MRI images in an intelligent manner. The concept of variable length in each harmony memory vector is applied...
This paper presents a new automatic initialization procedure for a level-set based segmentation algorithm that works on all slices for a given CT dataset. Level set segmentation algorithms provide promising results, are robust to dataset variations and do not require prior training. As such, they can be reliably used for segmentation of major organs in abdominal CT scans. However, level set algorithms...
Head injury is a significant economic, social and medical problem all over the world. Road accidents are the most frequent cause of head injury in Malaysia with highest risk in the young (15 to 24 years old). The associated outcomes include good recovery, possibility of death for the severely injured, which may cause disruption of the lives of their family members. It is important to predict the outcome...
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