Computer-aided diagnosis of mass-like lesion in breast MRI: Differential analysis of the 3-D morphology between benign and malignant tumors

This study aimed to evaluate the value of using 3-D breast MRI morphologic features to differentiate benign and malignant breast lesions. The 3-D morphological features extracted from breast MRI were used to analyze the malignant likelihood of tumor from ninety-five solid breast masses (44 benign and 51 malignant) of 82 patients. Each mass-like lesion was examined with regards to three categories of morphologic features, including texture-based gray-level co-occurrence matrix (GLCM) feature, shape, and ellipsoid fitting features. For obtaining a robust combination of features from different categories, the biserial correlation coefficient (|r_pb|) ≧ 0.4 was used as the feature selection criterion. Receiver operating characteristic (ROC) curve was used to evaluate performance and Student's t-test to verify the classification accuracy. The combination of the selected 3-D morphological features, including conventional compactness, radius, spiculation, surface ratio, volume covering ratio, number of inside angular regions, sum of number of inside and outside angular regions, showed an accuracy of 88.42% (84/95), sensitivity of 88.24% (45/51), and specificity of 88.64% (39/44), respectively. The A_Z value was 0.8926 for these seven combined morphological features. In conclusion, 3-D MR morphological features specified by GLCM, tumor shape and ellipsoid fitting were useful for differentiating benign and malignant breast masses.     

Detecting small pulmonary nodules with spiral ultrashort echo time sequences in 1.5 T MRI

Magnetic Resonance Materials in Physics, Biology and Medicine - This study investigated ultrashort echo time (UTE) sequences in 1.5 T magnetic resonance imaging (MRI) for small lung nodule...     

Interactions of heat and mass transfer in steam reheating of starchy foods

Steaming is a common practice in both household and industrial food processing; however, the process of heat transfer during steaming has not been fully explored. In this study, mathematical models that consider coupled energy, water and vapor transport were developed, and were solved using finite element software (COMSOL Multiphysics) for their application to the steam reheating of non-porous starch gel radish cake and steamed buns with porous matrices. Our simulation results indicated that the reheating of non-porous starch gel is a heat conduction process. During the reheating of the porous starch matrix, the infusion of condensate and evaporation–condensation mechanism contribute to steep sigmoid-shaped temperature profiles that are different from those of normal heat conduction. The validity of our mathematical model is corroborated by our experimental work of the steam reheating of samples with and without PE film wraps in a rice cooker. It shows a good agreement between the simulation and experimental results in terms of temperature and increased moisture. The implications of these models can provide a basis for future elucidation of more complicated food steaming processes.