Fully automated breast boundary and pectoral muscle segmentation in mammograms

Breast and pectoral muscle segmentation is an essential pre-processing step for the subsequent processes in Computer Aided Diagnosis (CAD) systems. Estimating the breast and pectoral boundaries is a difficult task especially in mammograms due to artifacts, homogeneity between the pectoral and breast regions, and low contrast along the skin-air boundary. In this paper, a breast boundary and pectoral muscle segmentation method in mammograms is proposed. For breast boundary estimation, we determine the initial breast boundary via thresholding and employ Active Contour Models without edges to search for the actual boundary. A post-processing technique is proposed to correct the overestimated boundary caused by artifacts. The pectoral muscle boundary is estimated using Canny edge detection and a pre-processing technique is proposed to remove noisy edges. Subsequently, we identify five edge features to find the edge that has the highest probability of being the initial pectoral contour and search for the actual boundary via contour growing. The segmentation results for the proposed method are compared with manual segmentations using 322, 208 and 100 mammograms from the Mammographic Image Analysis Society (MIAS), INBreast and Breast Cancer Digital Repository (BCDR) databases, respectively. Experimental results show that the breast boundary and pectoral muscle estimation methods achieved dice similarity coefficients of 98.8% and 97.8% (MIAS), 98.9% and 89.6% (INBreast) and 99.2% and 91.9% (BCDR), respectively

Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart Environment

To provide accurate activity recognition within a smart environment, visible spectrum cameras can be used as data capture devices in solution applications. Privacy, however, is a significant concern with regards to monitoring in a smart environment, particularly with visible spectrum cameras. Their use, therefore, may not be ideal. The need for accurate activity recognition is still required and so an unobtrusive approach is addressed in this research highlighting the use of a thermopile infrared sensor as the sole means of data collection. Image frames of the monitored scene are acquired from a thermopile infrared sensor that only highlights sources of heat, for example, a person. The recorded frames feature no discernable characteristics of people; hence privacy concerns can successfully be alleviated. To demonstrate how thermopile infrared sensors can be used for this task, an experiment was conducted to capture almost 600 thermal frames of a person performing four single component activities. The person’s position within a room, along with the action being performed, is used to appropriately predict the activity. The results demonstrated that high accuracy levels, 91.47%, for activity recognition can be obtained using only thermopile infrared sensors

Molecular genetics of 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11.2DS) is a congenital malformation and neuropsychiatric disorder caused by meiotic chromosome rearrangements. One of the goals of this review is to summarize the current state of basic research studies of 22q11.2DS. It highlights efforts to understand the mechanisms responsible for the 22q11.2 deletion that occurs in meiosis. This mechanism involves the four sets of low copy repeats (LCR22) that are dispersed in the 22q11.2 region and the deletion is mediated by nonallelic homologous recombination events. This review also highlights selected genes mapping to the 22q11.2 region that may contribute to the typical clinical findings associated with the disorder and explain that mutations in genes on the remaining allele can uncover rare recessive conditions. Another important aspect of 22q11.2DS is the existence of phenotypic heterogeneity. While some patients are mildly affected, others have severe medical, cognitive, and/or psychiatric challenges. Variability may be due in part to the presence of genetic modifiers. This review discusses current genome‐wide efforts to identify such modifiers that could shed light on molecular pathways required for normal human development, cognition or behavior