Search results for "Clustering"
showing 10 items of 446 documents
A fully automatic 2D segmentation method for uterine fibroid in MRgFUS treatment evaluation
2015
PurposeMagnetic Resonance guided Focused UltraSound (MRgFUS) represents a non-invasive surgical approach that uses thermal ablation to treat uterine fibroids. After the MRgFUS treatment, an operator must manually segment the treated fibroid areas to evaluate the NonPerfused Volume (NPV). This manual approach is operator-dependent, introducing issues of result reproducibility, which could lead to errors in the subsequent follow-up phase. Moreover, manual segmentation is time-consuming, and can have a negative impact on the optimization of both machine-time and operator-time. MethodTo address these issues, in this paper a novel fully automatic method based on the unsupervised Fuzzy C-Means cl…
U-search: a meta engine for creation of knowledge paths on the web
2010
The main tools used to find digital contents in the Web are search engines and directories but they are not presently able to understand the user specific needs and starting knowledge. This work presents "U-Search" a new meta engine that allows to create knowledge paths on the Web based on specific user requirements and knowledge levels. To this end, we consider different searcher categories such as a "basic searcher" who knows little about a topic and will look for more information, a "deep searcher" who will look for specific details on a topic that he/she already knows and a "wide searcher" who will look for expanding his/her knowledge domain with topics that are loosely related to the s…
A web search methodology for different user typologies
2009
Search engines and directories are the main tools used to find desired information into the ocean of digital contents that is the Web. However, they are not presently able to understand the user specific needs and starting knowledge because their inability to simulate the processes of human mind. Natural Language Processing, Folksonomy, Semantic Web and Serendipitous Surfing are some of the recent research fields towards understanding of human natural language and in general of real user needs. This work aims to add one step more to this evolution path by presenting a new search methodology that allows users to create new knowledge paths on the web based on their specific requirements. Thus…
Clinical support in radiation therapy scenarios: MR brain tumor segmentation using an unsupervised fuzzy C-Means clustering technique
2016
NeXt for neuro-radiosurgery: A fully automatic approach for necrosis extraction in brain tumor MRI using an unsupervised machine learning technique
2017
Stereotactic neuro-radiosurgery is a well-established therapy for intracranial diseases, especially brain metastases and highly invasive cancers that are difficult to treat with conventional surgery or radiotherapy. Nowadays, magnetic resonance imaging (MRI) is the most used modality in radiation therapy for soft-tissue anatomical districts, allowing for an accurate gross tumor volume (GTV) segmentation. Investigating also necrotic material within the whole tumor has significant clinical value in treatment planning and cancer progression assessment. These pathological necrotic regions are generally characterized by hypoxia, which is implicated in several aspects of tumor development and gro…
Patient Profiling Based on Spectral Clustering for an Enhanced Classification of Patients with Tension-Type Headache
2020
Profiling groups of patients in clusters can provide meaningful insights into the features of the population, thus helping to identify people at risk of chronification and the development of specific therapeutic strategies. Our aim was to determine if spectral clustering is able to distinguish subgroups (clusters) of tension-type headache (TTH) patients, identify the profile of each group, and argue about potential different therapeutic interventions. A total of 208 patients (n = 208) with TTH participated. Headache intensity, frequency, and duration were collected with a 4-week diary. Anxiety and depressive levels, headache-related burden, sleep quality, health-related quality of life, pre…
Determination of the Time Window of Event-Related Potential Using Multiple-Set Consensus Clustering
2020
Clustering is a promising tool for grouping the sequence of similar time-points aimed to identify the attention blocks in spatiotemporal event-related potentials (ERPs) analysis. It is most likely to elicit the appropriate time window for ERP of interest if a suitable clustering method is applied to spatiotemporal ERP. However, how to reliably estimate a proper time window from entire individual subjects’ data is still challenging. In this study, we developed a novel multiset consensus clustering method in which several clustering results of multiple subjects were combined to retrieve the best fitted clustering for all the subjects within a group. Then, the obtained clustering was processed…
Determination of the Time Window of Event-Related Potential Using Multiple-Set Consensus Clustering
2020
Clustering is a promising tool for grouping the sequence of similar time-points aimed to identify the attention blocks in spatiotemporal event-related potentials (ERPs) analysis. It is most likely to elicit the appropriate time window for ERP of interest if a suitable clustering method is applied to spatiotemporal ERP. However, how to reliably estimate a proper time window from entire individual subjects’ data is still challenging. In this study, we developed a novel multiset consensus clustering method in which several clustering results of multiple subjects were combined to retrieve the best fitted clustering for all the subjects within a group. Then, the obtained clustering was processed…
Tensor clustering on outer-product of coefficient and component matrices of independent component analysis for reliable functional magnetic resonance…
2019
Background. Stability of spatial components is frequently used as a post-hoc selection criteria for choosing the dimensionality of an independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data. Although the stability of the ICA temporal courses differs from that of spatial components, temporal stability has not been considered during dimensionality decisions. New method. The current study aims to (1) develop an algorithm to incorporate temporal course stability into dimensionality selection and (2) test the impact of temporal course on the stability of the ICA decomposition of fMRI data via tensor clustering. Resting state fMRI data were analyzed with two popu…
The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoenc…
2022
Funding Information: This work was financially supported by the Academy of Finland (Finnish Center of Excellence in Computational Inference Research COIN and grants #292334, #294238 to SK; #255349, #315553 to RS; #257576 to JK; #286405 funding for TM), the Sigrid Jusélius Foundation (grant to RS), the Finnish Cultural Foundation (grant to ML), the Swedish Cultural Foundation in Finland (grant to ML), the Maud Kuistila Memorial Foundation (grant to ML), and Aalto Brain Center. Publisher Copyright: Copyright © 2022 Mononen, Kujala, Liljeström, Leppäaho, Kaski and Salmelin. Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relat…