Technology of swallowable capsule for medical applications

Medical technology has undergone major breakthroughs in recent years, especially in the area of the examination tools for diagnostic purposes. This paper reviews the swallowable capsule technology in the examination of the gastrointestinal system for various diseases. The wireless camera pill has created a more advanced method than many traditional examination methods for the diagnosis of gastrointestinal diseases such as gastroscopy by the use of an endoscope. After years of great innovation, commercial swallowable pills have been produced and applied in clinical practice. These smart pills can cover the examination of the gastrointestinal system and not only provide to the physicians a lot more useful data that is not available from the traditional methods, but also eliminates the use of the painful endoscopy procedure. In this paper, the key state-of-the-art technologies in the existing Wireless Capsule Endoscopy (WCE) systems are fully reported and the recent research progresses related to these technologies are reviewed. The paper ends by further discussion on the current technical bottlenecks and future research in this area

REGION-COLOR BASED AUTOMATED BLEEDING DETECTION IN CAPSULE ENDOSCOPY VIDEOS

Capsule Endoscopy (CE) is a unique technique for facilitating non-invasive and practical visualization of the entire small intestine. It has attracted a critical mass of studies for improvements. Among numerous studies being performed in capsule endoscopy, tremendous efforts are being made in the development of software algorithms to identify clinically important frames in CE videos. This thesis presents a computer-assisted method which performs automated detection of CE video-frames that contain bleeding. Specifically, a methodology is proposed to classify the frames of CE videos into bleeding and non-bleeding frames. It is a Support Vector Machine (SVM) based supervised method which classifies the frames on the basis of color features derived from image-regions. Image-regions are characterized on the basis of statistical features. With 15 available candidate features, an exhaustive feature-selection is followed to obtain the best feature subset. The best feature-subset is the combination of features that has the highest bleeding discrimination ability as determined by the three performance-metrics: accuracy, sensitivity and specificity. Also, a ground truth label annotation method is proposed in order to partially automate delineation of bleeding regions for training of the classifier. The method produced promising results with sensitivity and specificity values up to 94%. All the experiments were performed separately for RGB and HSV color spaces. Experimental results show the combination of the mean planes in red and green planes to be the best feature-subset in RGB (Red-Green-Blue) color space and the combination of the mean values of all three planes of the color space to be the best feature-subset in HSV (Hue-Saturation-Value)

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine