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Full-Text Articles in Medicine and Health Sciences
Set-Based Cascading Approaches For Magnetic Resonance (Mr) Image Segmentation (Scamis), Jiang Liu, Tze-Yun Leong, Kin Ban Chee, Boon Pin Tan, Borys Shuter, Shih Chang Wang
Set-Based Cascading Approaches For Magnetic Resonance (Mr) Image Segmentation (Scamis), Jiang Liu, Tze-Yun Leong, Kin Ban Chee, Boon Pin Tan, Borys Shuter, Shih Chang Wang
Research Collection School Of Computing and Information Systems
This paper introduces Set-based Cascading Approach for Medical Image Segmentation (SCAMIS), a new methodology for segmentation of medical imaging by integrating a number of algorithms. Existing approaches typically adopt the pipeline methodology. Although these methods provide promising results, the results generated are still susceptible to over-segmentation and leaking. In our methodology, we describe how set operations can be utilized to better overcome these problems. To evaluate the effectiveness of this approach, Magnetic Resonance Images taken from a teaching hospital research programme have been utilised, to reflect the real world quality needed for testing in patient datasets. A comparison between the …
Batch Mode Active Learning And Its Applications To Medical Image Classification, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
Batch Mode Active Learning And Its Applications To Medical Image Classification, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
Research Collection School Of Computing and Information Systems
The goal of active learning is to select the most informative examples for manual labeling. Most of the previous studies in active learning have focused on selecting a single unlabeled example in each iteration. This could be inefficient since the classification model has to be retrained for every labeled example. In this paper, we present a framework for "batch mode active learning" that applies the Fisher information matrix to select a number of informative examples simultaneously. The key computational challenge is how to efficiently identify the subset of unlabeled examples that can result in the largest reduction in the Fisher …
Fortifying Password Authentication In Integrated Healthcare Delivery Systems, Yanjiang Yang, Robert H. Deng, Feng Bao
Fortifying Password Authentication In Integrated Healthcare Delivery Systems, Yanjiang Yang, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Integrated Delivery Systems (IDSs) now become a primary means of care provision in healthcare domain. However, existing password systems (under either the single-server model or the multi-server model) do not provide adequate security when applied to IDSs. We are thus motivated to present a practical password authentication system built upon a novel two-server model. We generalize the two-server model to an architecture of a single control server supporting multiple service servers, tailored to the organizational structure of IDSs. The underlying user authentication and key exchange protocols we propose are password-only, neat, efficient, and robust against off-line dictionary attacks mounted by …