Deep Learning Based Segmentation of Various Brain Lesions for Radiosurgery

Semantic segmentation of medical images with deep learning models is rapidly developed. In this study, we benchmarked state-of-the-art deep learning segmentation algorithms on our clinical stereotactic radiosurgery dataset, demonstrating the strengths and weaknesses of these algorithms in a fairly practical scenario. In particular, we compared the model performances with respect to their sampling method, model architecture, and the choice of loss functions, identifying the suitable settings for their applications and shedding light on the possible improvements

Redactable Signatures for Signed CDA Documents

[[abstract]]The Clinical Document Architecture, introduced by Health Level Seven, is a XML-based standard intending to specify the encoding, structure, and semantics of clinical documents for exchange. Since the clinical document is in XML form, its authenticity and integrity could be guaranteed by the use of the XML signature published by W3C. While a clinical document wants to conceal some personal or private information, the document needs to be redacted. It makes the signed signature of the original clinical document not be verified. The redactable signature is thus proposed to enable verification for the redacted document. Only a little research does the implementation of the redactable signature, and there still not exists an appropriate scheme for the clinical document. This paper will investigate the existing web-technologies and find a compact and applicable model to implement a suitable redactable signature for the clinical document viewer.[[notice]]補正完畢[[incitationindex]]SC

A Service-Oriented Healthcare Message Alerting Architecture in an Asia Medical Center: A Case Study

This paper illustrates how our development team has used some information technologies to let physicians obtain an instant abnormal laboratory result report for critical patient care services. We have implemented a healthcare message alerting system (HMAS) on a healthcare short message service (HSMS) engine and the distributed healthcare-oriented service environment (DiHOSE) in the National Taiwan University Hospital (NTUH). The HSMS engine has a general interface for all applications which could easily send any kind of alerting messages. Fundamentally, the DiHOSE uses HL7 standard formats to process the information exchange behaviors and can be flexibly extended for reasonable user requirements. The disease surveillance subsystem is an integral part of NTUH new hospital information system which is based on DiHOSE and the disease surveillance subsystem would send alerting messages through the HSMS engine. The latest cell phone message alerting subsystem, a case study, in NTUH proved that the DiHOSE could integrate the user required functions without much work. We concluded that both HSMS and DiHOSE can generalize and extend application demands efficiently

Application of Portable CDA for Secure Clinical-document Exchange

Abstract Health Level Seven (HL7) organization published the Clinical Document Architecture (CDA) for exchanging documents among heterogeneous systems and improving medical quality based on the design method in CDA. In practice, although the HL7 organization tried to make medical messages exchangeable, it is still hard to exchange medical messages. There are many issues when two hospitals want to exchange clinical documents, such as patient privacy, network security, budget, and the strategies of the hospital. In this article, we propose a method for the exchange and sharing of clinical documents in an offline model based on the CDA-the Portable CDA. This allows the physician to retrieve the patient's medical record stored in a portal device, but not through the Internet in real time. The security and privacy of CDA data will also be considered

Center of Mass-Based Adaptive Fast Block Motion Estimation

This work presents an efficient adaptive algorithm based on center of mass (CEM) for fast block motion estimation. Binary transform, subsampling, and horizontal/vertical projection techniques are also proposed. As the conventional CEM calculation is computationally intensive, binary transform and subsampling approaches are proposed to simplify CEM calculation; the binary transform center of mass (BITCEM) is then derived. The BITCEM motion types are classified by percentage of (0, 0) BITCEM motion vectors. Adaptive search patterns are allocated according to the BITCEM moving direction and the BITCEM motion type. Moreover, the BITCEM motion vector is utilized as the initial search point for near-still or slow BITCEM motion types. To support the variable block sizes, the horizontal/vertical projections of a binary transformed macroblock are utilized to determine whether the block requires segmentation. Experimental results indicate that the proposed algorithm is better than the five conventional algorithms, that is, three-step search (TSS), new three-step search (N3SS), four three-step search (4SS), block-based gradient decent search (BBGDS), and diamond search (DS), in terms of speed or picture quality for eight benchmark sequences