Development of a prognostic nomogram for identifying those factors which influence the 2- and 5-year survival chances of Taiwanese women diagnosed with breast cancer.

Breast cancer is one of the main causes of death for women throughout the world. The objective of this study is to identify significant factors of patients and their tumours that can be used to predict a 5-year survival status for Asian women. Patients who had been diagnosed with invasive breast carcinoma and undergone mastectomy were selected (n= 1016). Patient characteristics and outcome variables were also retrieved. A nomogram was created and its performance was evaluated by calculating its discrimination (concordance index), calibration, and by subsequent internal validation. The median follow-up was 39 months and mean overall survival was 62.5 months. Independent predictors of overall survival included in the nomogram were age, tumour size, lymph node involvement, metastasis and oestrogen receptor status. The concordance index was 0.80 and the calibration was excellent with all observed outcomes within the 95% CI of each predicted survival probability. The nomogram model was developed to predict the probability of survival in patients with breast cancer and should be useful for counselling patients and establishing appropriate surveillance strategies for Asian women.

Automatic MRI meningioma segmentation using estimation maximization.

With the advancement of the imaging facility and image processing technique, computer assisted surgical planning and image guided technology have become increasingly used in neurosurgery. For MRI has the characteristic of multi-spectral image data., so knowledge-base techniques is widely used in brain MRI segmentation. Here we recognize the location of the tumor automatically and provide an accurate result by Estimation Maximization method. Simultaneously, promote the efficiency of reading image as well.