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Virtual reality has the advantage to provide rich sensory feedbacks for training balance function. This study tested if the home-based virtual reality balance training is more effective than the conventional home balance training in improving balance, walking, and quality of life in patients with Parkinson's disease (PD). Methods: Twenty-three patients with idiopathic PD were recruited and underwent twelve 50-minute training sessions during the 6-week training period. The experimental group (n = 11) was trained with a custom-made virtual reality balance training system, and the control group (n = 12) was trained by a licensed physical therapist. Outcomes were measured at Week 0 (pretest), Week 6 (posttest), and Week 8 (follow-up). The primary outcome was the Berg Balance Scale. The secondary outcomes included the Dynamic Gait Index, timed Up-and-Go test, Parkinson's Disease Questionnaire, and the motor score of the Unified Parkinson's Disease Rating Scale. Results: The experimental and control groups were comparable at pretest. After training, both groups performed better in the Berg Balance Scale, Dynamic Gait Index, timed Up-and-Go test, and Parkinson's Disease Questionnaire at posttest and follow-up than at pretest. However, no significant differences were found between these two groups at posttest and follow-up. Conclusion: This study did not find any difference between the effects of the home-based virtual reality balance training and conventional home balance training. The two training options were equally effective in improving balance, walking, and quality of life among community-dwelling patients with PD.

This paper introduces a multi-level morphological active contour (MMAC) algorithm to identify and delineate tree crowns in mountainous forest based on rasterized airborne lidar data. MMAC is a generalized tree crown mapping algorithm which can accommodate multiple heads in a crown as well as overlapping crowns. The MMAC algorithm comprises three steps: bottom up erosion (BUE) which identifies stand candidates, top down dilation (TDD) which estimates the crown periphery, and an active contour model (ACM) which delineates crown contours. Three sample plots were selected in Alishan National Scenic Area, Taiwan, (predominantly alder, sugi, and red cypress) for evaluation of the algorithm. When compared with ground survey data, the algorithm achieved an average detection accuracy of 24 percent omission error and 13 percent commission error in identifying individual trees in mountainous forest stands. Detection accuracy is potentially related to stand density. [ABSTRACT FROM AUTHOR]

The simplex growing algorithm (SGA) was recently developed as an alternative to the N-finder algorithm (N-FINDR) and shown to be a promising endmember extraction technique. This paper further extends the SGA to a versatile real-time (RT) processing algorithm, referred to as RT SGA, which can effectively address the following four major issues arising in the practical implementation for N-FINDR: 1) use of random initial endmembers which causes inconsistent final results; 2) high computational complexity which results from an exhaustive search for finding all endmembers simultaneously; 3) requirement of dimensionality reduction because of large data volumes; and 4) lack of RT capability. In addition to the aforementioned advantages, the proposed RT SGA can also be implemented by various criteria in endmember extraction other than the maximum simplex volume. [ABSTRACT FROM AUTHOR]

A pilot system for a mammography tele-consultation in TaiChung Veterans General Hospital (TCVGH), Taiwan is proposed in this paper. It is developed and designed based on a distributed system and implemented in a top-down high speed network hierarchy with communication security. It is also integrated with specific diagnostic tools and collaboration awareness tools currently available in TCVGH and linked with the external internet, Taiwan Academic Network (TANet) that will be upgraded into the next generation, TANet2 in the next five years. The distributed system is designed using a JAVA-based remote method invoking system. It allows the transport of images through a firewall combined with peripheral applications that include a Digital Imaging and Communications in Medicine (DICOM) server for image transmission, Picture Archiving and Communication System (PACS), Hospital Information System (HIS) and computer-aided diagnostic systems via a Java native interface. The communication security is implemented using ElGamal's public-key cryptosystem for identifications of authorization. Finally the specific mammography diagnostic tools and collaboration awareness tools demonstrated in the proposed system are developed in accordance with the Breast Imaging Reporting And Data System (BI-RADS) suggested by the American College of Radiology. [ABSTRACT FROM AUTHOR]