22 research outputs found
A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement
Background: Low intensity transcranial electrical stimulation (tES), including alternating or direct current stimulation (tACS or tDCS), applies weak electrical stimulation to modulate the activity of brain circuits. Integration of tES with concurrent functional magnetic resonance imaging (fMRI) allows for the mapping of neural activity during neuromodulation, supporting causal studies of both brain function and tES effects. Methodological aspects of tES-fMRI studies underpin the results, and reporting them in appropriate detail is required for reproducibility and interpretability. Despite the growing number of published reports, there are no consensus-based checklists for disclosing methodological details of concurrent tES-fMRI studies. Objective: To develop a consensus-based checklist of reporting standards for concurrent tES-fMRI studies to support methodological rigor, transparency, and reproducibility (ContES Checklist). Methods: A two-phase Delphi consensus process was conducted by a steering committee (SC) of 13 members and 49 expert panelists (EP) through the International Network of the tES-fMRI (INTF) Consortium. The process began with a circulation of a preliminary checklist of essential items and additional recommendations, developed by the SC based on a systematic review of 57 concurrent tES-fMRI studies. Contributors were then invited to suggest revisions or additions to the initial checklist. After the revision phase, contributors rated the importance of the 17 essential items and 42 additional recommendations in the final checklist. The state of methodological transparency within the 57 reviewed concurrent tES-fMRI studies was then assessed using the checklist. Results: Experts refined the checklist through the revision and rating phases, leading to a checklist with three categories of essential items and additional recommendations: (1) technological factors, (2) safety and noise tests, and (3) methodological factors. The level of reporting of checklist items varied among the 57 concurrent tES-fMRI papers, ranging from 24% to 76%. On average, 53% of checklist items were reported in a given article. Conclusions: Use of the ContES checklist is expected to enhance the methodological reporting quality of future concurrent tES-fMRI studies, and increase methodological transparency and reproducibility
Fully automatic identification and discrimination of sperm’s parts in microscopic images of stained human semen smear
Mean values of lesion volumes (LV), similarity criteria and mean value of segmentation time (T) for each patient data and for all images in data set (last line of the table) obtained using the proposed method.
<p>Mean values of lesion volumes (LV), similarity criteria and mean value of segmentation time (T) for each patient data and for all images in data set (last line of the table) obtained using the proposed method.</p
Brain tissue segmentation examples, using the three-level threshold.
<p>Each column shows the result of segmentation for a brain image with different lesion load. (a) Shows the original brain images. (b) The obtained member functions plots. (c) Shows the segmentation results using the three-level thresholding (maximum fuzzy entropy approach). (d) Dark membership images. (e) Medium membership images. (f) Bright membership images. (For interpretation of the references to color in this figure, the reader is referred to the web version of this article.)</p
Similarity index (SI) values for the proposed method and the other methods.
<p>s: slices, v: volume.</p><p>The reader is referred to the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065469#pone.0065469-Llad1" target="_blank">[9]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065469#pone.0065469-Mortazavi1" target="_blank">[58]</a> for complete explanations about methods reported here.</p
Block diagram of the proposed approach for fully automatic segmentation of MS lesions.
<p>Block diagram of the proposed approach for fully automatic segmentation of MS lesions.</p
A typical Infratentorial lesion.
<p>(a) PD-w, (b) T2-w, (c) and FLAIR images of a patient with remitting relapsing multiple sclerosis (RRMS) demonstrate a pontine lesion (arrows) that is not demonstrated on the FLAIR sequence <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065469#pone.0065469-Sahraian1" target="_blank">[2]</a>.</p
The average of the Jaccard Scores for different values of the BM parameter (in the interval [0.01, 0.1]).
<p>The average of the Jaccard Scores for different values of the BM parameter (in the interval [0.01, 0.1]).</p
Segmentation of CSF areas.
<p>(a) Shows a typical brain image. (b) Dark membership image (to give more understanding, the obtained image has been inverted). (c) Result of applying the localized-weighted filter to dark membership image (the inverted result). (d) : CSF areas obtained from filtered dark membership image. (e) : CSF areas obtained from dark membership image. (g) Result of CSF segmentation. (For interpretation of the references to color in this figure, the reader is referred to the web version of this article).</p