PURPOSE Tract-specific analysis (TSA) measures diffusion parameters along a specific fiber that has been extracted by fiber tracking using manual regions of interest (ROIs), but TSA is limited by its requirement for manual operation, poor reproducibility, and high time consumption. We aimed to develop a fully automated extraction method for the cingulum bundle (CB) and to apply the method to TS...

Coronavirus Disease 2019 or known as COVID-19 is a new disease that can cause respiratory problems and pneumonia. This caused by infection with Severe Acute Respiratory Syndrome Me 2 (SARS-CoV-2). Some of the clinical symptoms appear vary, ranging from such influenza, cough, cold, throat pain, muscle aches, headaches to those serious complications pneumonia sepsis. research build case-based rea...

The extraction of consensus segmentations from several binary or probabilistic masks is important to solve various tasks such as the analysis inter-rater variability fusion neural network outputs. One most widely used method obtain a segmentation STAPLE algorithm. In this paper, we first demonstrate that output algorithm heavily impacted by background size images and choice prior. We then propo...

This paper describes a coreference annotation scheme, coreference annotation specific issues and their solutions through our proposed annotation scheme for Hindi. We introduce different co-reference relation types between continuous mentions of the same coreference chain such as ‘Part-of’, ‘Function-value pair’ etc. We used Jaccard similarity based Krippendorff‘s’ alpha to demonstrate consisten...

Our purpose in this study is to develop a scheme to segment the rectus abdominis muscle region in X-ray CT images. We propose a new muscle recognition method based on the shape model. In this method, three steps are included in the segmentation process. The first is to generate a shape model for representing the rectus abdominis muscle. The second is to recognize anatomical feature points corre...

The Jaccard index is an important similarity measure for item sets and Boolean data. On large datasets, an exact similarity computation is often infeasible for all item pairs both due to time and space constraints, giving rise to faster approximate methods. The algorithm of choice used to quickly compute the Jaccard index |A∩B| |A∪B| of two item sets A and B is usually a form of min-hashing. Mo...

In many industrial applications of big data, the Jaccard Similarity Computation has been widely used to measure the distance between two profiles or sets respectively owned by two users. Yet, one semi-honest user with unpredictable knowledge may also deduce the private or sensitive information (e.g., the existence of a single element in the original sets) of the other user via the shared simila...