Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.
The effect of biochar substituted for anthracite as reductant on magnetizing-roasting pyrite cinder was investigated.The key of magnetizing-roasting is the gasification reaction between reductants and CO2.Since biochar could react with CO2 more rapidly at lower temperature,the reactivity of biochar is better than that of anthracite.The gasification of biochar could produce reducing condition ofφCO/(φCO+φCO2)about 10%-20% between 700-800 ℃,which is in accord with the atmosphere and temperature of Fe2O3 reduction.So it is beneficial to the reduction of iron mineral of pyrite cinder.Compared with anthracite,biochar could decrease the roasting temperature from825 to 750 ℃ and roasting time from 20 to 15min,which shows that a better effect of magnetization could be obtained in the condition of lower temperature and shorter time.Using biochar as reductant,iron concentrate extracted from pyrite cinder as about 64%iron grade could be produced,and the recovery is over 90% under the condition of above 90% grinding particle less than 0.045 mm and magnetic intensity of 0.124-0.194 T. 相似文献