Purpose: Online adaptive correction in image-guided intensity-modulated radiotherapy appears to be a promising approach for precision radiation treatment in head-and-neck tumors. This research is designed to evaluate the setup uncertainties in the left-right (L-R), superior-inferior (S-I), and anterior-posterior (A-P) directions and rotational variations: pitch, roll, and yaw for head-and-neck cancer (HNC) patients with the ExacTrac 6 degree-of-freedom (6D) image-guided radiotherapy (IGRT) system. Materials and Methods: The setup errors measured by ExacTrac 6D IGRT system at the treatment unit with respect to the planning computed tomography were recorded for 40 patients with head-and-neck tumors. The residual setup errors were computed and quantitatively analyzed. Results: The results indicated that the setup errors measured in the S-I direction were larger than the other two directions. For the three rotational angles, the results were very close. The verifications showed that after the first correction, the overall setup errors were generally <0.32 mm in the L-R, S-I, and A-P directions and <0.2° in the three rotational variations: pitch, roll, and yaw. According to the results of verifications, we know that ExacTrac 6D IGRT system was accurate and clinical feasibility. Conclusion: The results of our study have shown that daily image guidance with ExacTrac 6D image-guided system for HNC patients is effective. These data suggest it allows a high accurate of setup errors.

Background and Objective: Portable and readily accessible wellness devices can aid vital sign measuring for those interested in tracking their health. In this diagnostic accuracy study, we evaluated the performance of the VitalWellness device (VW), a wireless, compact, noninvasive device that measures four vital signs (VS) – blood pressure (BP), heart rate (HR), respiratory rate (RR), and body temperature (BT) – using the index finger and forehead. Methods: Adult volunteers with VS that fell both within and outside of the normal physiological range were enrolled to provide BP, HR, RR, and BT measurements using both the VW and Food and Drug Administration-approved reference devices. A subgroup of participants underwent an additional test to analyze the VW's performance on HR and RR outside of normal physiological ranges. Statistical measurements were plotted on scatter and Bland–Altman plots. Sensitivity analyses to evaluate the VW's performance by gender, skin color, finger size, and auxiliary activities were performed. Results: A total of 263 participants completed the study. On an average, systolic BP measured using the VW was 10 mmHg lower than that of the reference device (correlation coefficient r = 0.7), whereas diastolic BP was 3 mmHg lower (r = 0.6), and RR was 2 bpm lower (r = 0.7). VW HR and BT measurements were, on average, 1 bpm and 0.3°F higher than the corresponding reference measurements (r = 0.9 and r = 0.3), respectively. Conclusion: The VW device is well-suited for home-based, nonmedical monitoring of HR, RR, and BP. Further improvement in measurement accuracy is required to enable applications for medical use.

Psychophysiological decompensation as a result of occupational stress leads to impairment of occupational performance. Adequate recovery from psychological stress is necessary to maintain occupational performance. It is possible to measure the psychophysiological status and recovery during sleep with health data streamed from biomedical digital devices. Such data, with reference to heart and sleep parameters, could be processed to reflect health status and whether there is a risk of psychophysiological decompensation. This article describes the interpretation of resting heart rate measures, heart rate variability, and actigraphy measures during regular sleep in relation to psychological stress. Interpretation of the health data should be done by informed health-care professionals in combination with clinical history taking. The article does not cover digital measurements while awake and active. The aim of this review article is to provide an evidence-based rationale to health professionals how to interpret digital health data profiles from biomedical devices in appraising psychological stress and recovery. The objective is to prevent the adverse impact of psychological stress on health. Specific lifestyle measures and therapy to manage psychological stress, such as exercise, diet, and cognitive behavioral therapy for insomnia, are not discussed in this article. Applications are especially relevant in the field of occupational health in preventing occupational burnout, achieving a healthy work–life balance, and sustaining a healthy working life. There are future implications with regard to disease prevention as a large proportion of chronic diseases, for example, hypertension, diabetes depression, and ischemic heart disease, are related to chronic psychological stress. Stress monitoring with biomedical devices should occur over periods of work and nonwork days.

Background and Objectives: Image segmentation is the basic problem in computer vision and pattern recognition. This study mainly focuses on the segmentation of medical sequence images. Materials and Methods: In this article, we considered the spatial similarity of the medical sequence image in active contour model (ACM) for segmentation. First, by utilizing the similarity of object contour between adjacent slices of medical images, and then using the segment result of the former slice as the initial contour of the next image to segmentation. The proposed model can automatically obtain a better initial contour location and reduce the computing cost for segment processing. Second, to improve the accuracy of image segmentation, we considered the similarity of the object contour between adjacent slices, and introduce a punishment term in localized ACM. Results: We compared our model and other methods for segmenting medical brain magnetic resonance slices, and the experimental results on synthetic medical sequence images validate the effectiveness of the proposed method. Conclusions: By utilizing the similarity of object contour between adjacent slices of medical images, and using the segment result of former slice as the initial contour of the next image to segment, the proposed model can obtain better initial contour location for segmentation sequence images and reduce the computing cost for whole medical sequence image segmentation process.

Background and Objectives: Point set registration is a very fundamental problem in computer vision. The registration problem can be divided into rigid and nonrigid registration. The transformation function modeling of rigid registration is simpler, whereas the nonrigid registration is better to solve the practical problems. Materials and Methods: We proposed a robust point set registration method using both global and local structures. Here, we use a popular probability model, Gaussian mixture model, to preserve the global structure of point set. Then, we designed a local constraint provided by some neighboring points to maintain the local structure of the point set. Finally, expectation–maximization algorithm is used to update model parameters in our method. Results: First of all, we carried out experiments on the synthesized data, which included four degradation cases: deformation, noise, outlier, and rotation. By comparing the mean and standard deviation of registration errors with the several state-of-the-art methods, our method was proved to have stronger robustness. Then, we conducted experiments on real retinal fundus images, aiming to establish reliable feature point correspondence between the two images. The experimental results show that we perform better when the two images have larger shooting angles and more noises. Conclusions: The Gaussian mixture protects the global structure of the point set, and the local constraints make full use of the local structure, which makes our method more robust. Experiments on synthetic data prove that our method obtains superior results to those of the state-of-the-art methods. Experiments on retinal image data show that our method also performs very well in practical applications.

Background and Objectives: In magnetic resonance (MR) images' quantitative analysis, there are often considerable difficulties due to factors, such as intensity inhomogeneities and low contrast. Here, we construct a new image segmentation method to solve the MR image segmentation problem caused by internal and external factors. Materials and Methods: We downloaded a series of MR images as research objects through the BrainWeb (http://www.bic.mni.mcgill.ca/brainweb/). There is low contrast information between different components in these images. In addition, we randomly added a certain degree of bias field information to the images. We proposed a model that can simultaneously perform bias field estimation and image segmentation. Our idea is to make use of the property that observed image can be decomposed into multiplicative components. First, the bias field representation is given by a series of smooth basic functions; the required true image is represented as the function of observed image and bias field. Then, the segmentation model of Gaussian probability distribution with different means and variances is constructed by local information. Results: Qualitative experiments (intensity inhomogeneity images) show that our model achieves satisfactory segmentation results with very few (<10) iterations for severe intensity inhomogeneities image segmentation, while quantitative experiments (20 brain MR images) show that the proposed model can achieve higher accuracy in segmentation. Conclusions: Different from the existing model, our model is constructed based on the local information of the true image, and the influence of above-mentioned factors is better avoided and obtain satisfactory results.

Background and Objectives: Stroke is a leading cause of long-term disability. Rehabilitation involving repetitive, high-intensity, and task-specific exercise is the pathway to restore motor skills. Robotic assistive devices such as Gloreha are increasingly being used in upper limb rehabilitation. The aim of this study is to explore the efficacy of robotic therapy for upper limb rehabilitation using robotic glove (Gloreha) in patients with stroke. Materials and Methods: The patients affected by stroke who were admitted to our rehabilitation unit were studied. Patients were exposed to Gloreha device rehabilitation (30 min/die), physiotherapy (1,5 hours/die), and occupational therapy (30 min/die). We measured the impairment in motor function and muscle tone using the modified Ashworth scale (MAS), the activities of daily living functional independence measure (FIM), and the finger dexterity Nine-Hole Peg test (NHPT). Results: Twelve patients (mean age = 64.5 years; male/female: 8:4) were admitted at the rehabilitation training. We found statistically significant differences between admission and discharged in terms of functional recovery using the FIM scale (pre/M = 88.33; post/M = 117.25,P = 0.01); hand training showed a better outcome using the NHPT (pre/M = 51.8; post/M = 36.33, P = 0.01). No significant changes were observed in terms of spasticity with the MAS (pre/M = 1.25; post/M = 1.08;P > 0.05). Conclusions: Rehabilitation with robotic glove (Gloreha) can positively promote functional recovery of arm function in a patient with stroke.

Background and Objective: Oral cancer is a major public health problem which carries significant morbidity and mortality. A shift from treatment to prevention by screening is the key to reduce oral cancer lesion among population. Searching for an affordable and viable alternative to face-to-face screening that can expedite diagnosis of oral diseases among rural population with good accuracy is mandatory. One of the most realistic solutions to acknowledge this hurdle and the unavailability of dental professionals, is mobile teledentistry. Materials and Methods: Secondary data analysis was conducted, in which the data were derived from the project of “Oral Cancer Screening Program in Rural population” conducted by Thirumalai Mission Hospital, Ranipet. Ninety-six biopsies were taken for the patients who had visible oral lesions which had been provisionally diagnosed on clinical examination. Oral screening was carried out by unaided face-to-face screening method by a trained and calibrated dentist. In a separate subsequent visit, a trained teledental assistant took photographs of each participant's mouth by using a smartphone camera; the charting of the photographs was conducted independently by two dentists. Results: Intra-examiner reliability of Examiner 1 and Examiner 2 was 0.943 and 0.921, respectively. Inter examiner reliability score of 0.879 was obtained between both the examiners by the photographic method of diagnosis. Intraclass correlation coefficient between two methods of examination was 0.812. Agreement between the photographic examination (Examiner 1, Examiner 2) with the gold standard biopsy report was 0.791 and 0.855, respectively. Conclusion: Smartphone camera use offers a valid and reliable means of remote screening for oral lesions. Photographs of the oral lesions taken from the smart-phone camera with an acceptable diagnostic validity and reliability.

This article reviews the role of mimicking materials used in focused ultrasound surgery (FUS) under magnetic resonance imaging. FUS is a noninvasive surgery that has many applications in oncology and neurology. Phantoms (mimicking materials) are mostly based in agar or gelatin phantoms.

Background and Objectives: Multiple sclerosis (MS) lesion segmentation is important in estimating the progress of the disease and measuring the impact of new clinical treatments. Manual lesion delineation for the segmentation of lesions is time-consuming and suffers from observer variability. Therefore, a fully automated MS lesion segmentation method is considerable important in clinical practice. Subjects and Methods: In this study, we present a multilabel fusion embedded level set method for white matter lesion segmentation from MS patient images. Specifically, we focus on the validation of the variational level set method. Lesion segmentation is achieved by extending the level set contour which consists of an intensity-constrained term, an image data term, and a regularization term. Results: To compare the performance of our method with other state-of-the-art methods, we evaluated the methods with 25 magnetic resonance imaging datasets of MS patients. The dice score reaches an average of 0.55 for the proposed method. The sensitivity value and specificity value reach an average of 0.89 and 0.14, respectively. Conclusions: Experimental results demonstrate that our method is robust to parameter setting and outperforms other methods. The intensity-constrained term plays a key role in improving the segmentation accuracy. The experimental results show that our approach is effective and robust for lesion segmentation, which might simplify the quantification of lesions in basic research and even clinical trials.

Background and Objectives: Developing serious games (SGs) for children is challenging, especially when dealing with complex medical diagnosis. Enhancing children's compliance for the treatment of chronic conditions is a crucial challenge that requires caring about the engagement of users in the game experience already from the initial stages of the development. Materials and Methods: Participatory design is the methodological key to trace the right path toward an effective and easy-to-use game; specific methodological settings are necessary to collect meaningful feedback and guide the creation of the game. Our article reports the involvement of 14 young users in two different stages of the design and development of two SGs for chronic clinical conditions (Crohn's disease and cystic fibrosis). Results: Specific feedbacks were reported about game contents (e.g., the preference for anthropomorphic avatars) and technological issues (e.g., the need of a graphical tutorial). Conclusions: Using the same methodological approach in two different phases of the development allows to highlight children's perspective toward a technological solution addressing clinical compliance.

Background and Objectives: This study investigates a novel type of textile pressure sensor fabricated in a single production step. The work characterizes two designs of electronic textile pressure sensor creating new knowledge into the operation of these types of textile sensors. Interest in electronic flexible film and electronic textile pressure sensing has grown in recent years given their potential in medical applications, principally in developing monitoring solutions for wheelchair users and hospital patients to help prevent the formation of pressure ulcers. Materials and Methods: Two designs of textile pressure sensor were produced using computerized flat-bed knitting. One design was produced in a single step, where the conductive tracks were incorporated into the top and bottom surfaces of a knitted spacer structure (knitted spacer pressure sensor). The other sensor was comprised of separate knitted layers. The response of the sensors was tested by changing the applied pressure in two ways: By altering the applied force or changing the area of the applied force. Sensor hysteresis and how the sensor thickness affected its response were also examined. Results: The two sensor designs behaved differently under the tested conditions. The knitted spacer pressure sensor was pressure sensitive up to 25 kPa and showed no hysteretic effects over the pressure range of interest. Conclusions: This study presents a fully textile pressure sensor that was produced with a single production step and demonstrates its functionality over the pressure range of interest for monitoring wheelchair users.

Background and Objectives: Nowadays, more and more open source medical imaging databases are published on the Internet for medical teaching, algorithm development, and medical research. However, a statistical survey of these databases is still lacking. In this survey, we summarize the current status of open source medical image databases on the Internet. The aim is to make it easier for everyone to find and use open source medical image data. Methods: Information about publicly available medical image databases was collected by searching for scientific papers and Internet search engines. Based on the collected information, the number of databases and the number of images were counted for different diseases, body parts, imaging modalities, and countries. Results: Cancer, particularly breast cancer and lung cancer, ranked top in database numbers among all diseases. The breast, brain, lung, and chest are the top four body parts in terms of database numbers. Computed tomography, magnetic resonance imaging, and X-ray are the most common imaging modalities in the open source datasets. The USA and the Netherlands are the top two countries who own the most databases. Conclusions: The rankings for diseases and body parts were closely related to the diseases morbidity and the health-care expenditure of a country. The number of open sources of medical imaging databases is still growing; there is a need for continuous statistical research on their existence status in the coming years. The list of all the collected databases is opened on the Internet (https://docs.qq.com/sheet/DQWF0QlZKVHpHU1Za).

Advancements in technology have always had major impacts on medicine. Increased use of smartphone and related software applications has created a new era in clinical data exchange among patients and clinicians. Teledentistry is a combination of telecommunications and dentistry, involving the exchange of clinical information and images over remote distances for dental consultation and treatment planning. It has the potential to address many of the problems related to access, cost efficiency and quality of dental care. Through teleconsultation with specialists in larger communities, a dentist in a nearby community can provide access to specialty care for their patients easily. Teledentistry can extend care to underserved patient populations, such as those in rural areas, at a reasonable cost. This review article aims to emphasize the importance of teledentistry in various specialties of dentistry and its role in serving the underserved population.