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.
Three-dimensional (3D) YBO3:Tb3+ flower-like and dense flower-like hierarchitecture constituted of nanoflakes are solvothermally synthesized in the presence of polyborate precursors in the mixture of ethanol and water. The growth process of the YBO3:Tb3+ flowers and dense flowers was explored based on the time-dependent experiment and the results showed that the growth mechanism follows an in situ growth rather than self-assembly process as reported previously. YBO3:Tb3+ morphologies composed of nanoflakes are achieved by controlling the concentration of ethanol and dependence of photoluminescence on morphology was studied. Remarkable photoluminescence enhancement was observed for YBO3:Tb3+ with flower-like morphology demonstrating the potential of the microstructure in future applications as a green phosphor. Such a synthetic method and growth mechanism may be applied to fabricate complex 3D architectures of other materials. 相似文献
AbstractThe reabsorption characteristics of the lignite treated by low and high temperature drying process were addressed in the paper. The information about the moisture form, functional groups, effective water-filled porosities and equilibrium moisture content of the lignite before and after the drying process was investigated using Differential scanning calorimetry (DSC), Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy and a self-made reabsorption device, respectively. The results show that the low drying temperature (140, 190, 230?°C, 10?min, N2) has little impact on the effective water-filled porosities of the resulted samples, whereas it has a great influence on the main oxygen-containing functional groups, which amount firstly decreases and then increases with the drying temperature increasing. In the case of the lignite samples dried under high-temperature (600, 700, 800?°C, 30?s, N2), the amount of the effective water-filled porosity of the sample decreases and the amount of oxygen-containing functional groups increases as the temperature increasing. The reabsorption capability of the high temperature dried sample is much lower than that of the sample treated under low drying temperature. The reabsorption characteristics of the low-temperature dried samples are affected by the amount of the oxygen-containing functional groups, while the effective water-filled porosity is main factor for the lignite samples derived from high temperature drying process. Moreover, the work gives a good evidence that the high-temperature drying process is an effective choose for lignite upgrading. 相似文献