Example of International Journal of Biomedical Imaging format
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Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format
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Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format Example of International Journal of Biomedical Imaging format
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International Journal of Biomedical Imaging — Template for authors

Publisher: Hindawi
Categories Rank Trend in last 3 yrs
Radiology, Nuclear Medicine and Imaging #24 of 288 up up by 62 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 52 Published Papers | 409 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 02/06/2020
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Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

7.9

39% from 2019

CiteRatio for International Journal of Biomedical Imaging from 2016 - 2020
Year Value
2020 7.9
2019 5.7
2018 4.1
2017 3.4
2016 4.2
graph view Graph view
table view Table view

0.626

12% from 2019

SJR for International Journal of Biomedical Imaging from 2016 - 2020
Year Value
2020 0.626
2019 0.561
2018 0.38
2017 0.501
2016 0.532
graph view Graph view
table view Table view

3.203

112% from 2019

SNIP for International Journal of Biomedical Imaging from 2016 - 2020
Year Value
2020 3.203
2019 1.509
2018 1.313
2017 1.128
2016 1.371
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 39% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased by 12% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 112% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
International Journal of Biomedical Imaging

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Hindawi

International Journal of Biomedical Imaging

The last quarter century has witnessed major advancements that have brought biomedical imaging to a paramount status in life sciences. As a prominent example, the National Institute of Biomedical Imaging and Bioengineering (NIBIB) was established in 2000 as the newest institut...... Read More

Medicine

i
Last updated on
02 Jun 2020
i
ISSN
1687-4188
i
Impact Factor
Medium - 0.879
i
Acceptance Rate
47%
i
Frequency
Not provided
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
unsrt
i
Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker. “Specular andreev reflection in graphene”. Phys. Rev. Lett., vol. 97, no. 6, 067007, 2006.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1155/2012/940585
A review of indocyanine green fluorescent imaging in surgery

Abstract:

The purpose of this paper is to give an overview of the recent surgical intraoperational applications of indocyanine green fluorescence imaging methods, the basics of the technology, and instrumentation used. Well over 200 papers describing this technique in clinical setting are reviewed. In addition to the surgical applicati... The purpose of this paper is to give an overview of the recent surgical intraoperational applications of indocyanine green fluorescence imaging methods, the basics of the technology, and instrumentation used. Well over 200 papers describing this technique in clinical setting are reviewed. In addition to the surgical applications, other recent medical applications of ICG are briefly examined. read more read less

Topics:

Indocyanine green (53%)53% related to the paper
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1,000 Citations
open accessOpen access Journal Article DOI: 10.1155/2013/154860
Robust Vessel Segmentation in Fundus Images
Attila Budai1, Rüdiger Bock1, Andreas Maier1, Joachim Hornegger1, Georg Michelson1

Abstract:

One of the most common modalities to examine the human eye is the eye-fundus photograph. The evaluation of fundus photographs is carried out by medical experts during time-consuming visual inspection. Our aim is to accelerate this process using computer aided diagnosis. As a first step, it is necessary to segment structures i... One of the most common modalities to examine the human eye is the eye-fundus photograph. The evaluation of fundus photographs is carried out by medical experts during time-consuming visual inspection. Our aim is to accelerate this process using computer aided diagnosis. As a first step, it is necessary to segment structures in the images for tissue differentiation. As the eye is the only organ, where the vasculature can be imaged in an in vivo and noninterventional way without using expensive scanners, the vessel tree is one of the most interesting and important structures to analyze. The quality and resolution of fundus images are rapidly increasing. Thus, segmentation methods need to be adapted to the new challenges of high resolutions. In this paper, we present a method to reduce calculation time, achieve high accuracy, and increase sensitivity compared to the original Frangi method. This method contains approaches to avoid potential problems like specular reflexes of thick vessels. The proposed method is evaluated using the STARE and DRIVE databases and we propose a new high resolution fundus database to compare it to the state-of-the-art algorithms. The results show an average accuracy above 94% and low computational needs. This outperforms state-of-the-art methods. read more read less

Topics:

Fundus (eye) (54%)54% related to the paper, Segmentation (50%)50% related to the paper
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423 Citations
open accessOpen access Journal Article DOI: 10.1155/2017/9749108
Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction Using Biologically Inspired BWT and SVM
Nilesh Bhaskarrao Bahadure1, Arun Kumar Ray1, Har Pal Thethi2

Abstract:

The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to ... The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated Berkeley wavelet transformation (BWT) based brain tumor segmentation. Furthermore, to improve the accuracy and quality rate of the support vector machine (SVM) based classifier, relevant features are extracted from each segmented tissue. The experimental results of proposed technique have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 96.51% accuracy, 94.2% specificity, and 97.72% sensitivity, demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 0.82 dice similarity index coefficient, which indicates better overlap between the automated (machines) extracted tumor region with manually extracted tumor region by radiologists. The simulation results prove the significance in terms of quality parameters and accuracy in comparison to state-of-the-art techniques. read more read less

Topics:

Image segmentation (55%)55% related to the paper, Feature extraction (51%)51% related to the paper
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402 Citations
open accessOpen access Journal Article DOI: 10.1155/2013/323268
Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms

Abstract:

Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and class... Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique's performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided. read more read less
View PDF
294 Citations
open accessOpen access Journal Article DOI: 10.1155/2013/942353
Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies

Abstract:

This paper overviews one of the most important, interesting, and challenging problems in oncology, the problem of lung cancer diagnosis Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can increase the patient's chance of survival For this reason, CAD systems fo... This paper overviews one of the most important, interesting, and challenging problems in oncology, the problem of lung cancer diagnosis Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can increase the patient's chance of survival For this reason, CAD systems for lung cancer have been investigated in a huge number of research studies A typical CAD system for lung cancer diagnosis is composed of four main processing steps: segmentation of the lung fields, detection of nodules inside the lung fields, segmentation of the detected nodules, and diagnosis of the nodules as benign or malignant This paper overviews the current state-of-the-art techniques that have been developed to implement each of these CAD processing steps For each technique, various aspects of technical issues, implemented methodologies, training and testing databases, and validation methods, as well as achieved performances, are described In addition, the paper addresses several challenges that researchers face in each implementation step and outlines the strengths and drawbacks of the existing approaches for lung cancer CAD systems read more read less

Topics:

Computer-aided diagnosis (53%)53% related to the paper
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232 Citations
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International Journal of Biomedical Imaging format uses unsrt citation style.

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1. Can I write International Journal of Biomedical Imaging in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the International Journal of Biomedical Imaging guidelines and auto format it.

2. Do you follow the International Journal of Biomedical Imaging guidelines?

Yes, the template is compliant with the International Journal of Biomedical Imaging guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in International Journal of Biomedical Imaging?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the International Journal of Biomedical Imaging citation style.

4. Can I use the International Journal of Biomedical Imaging templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for International Journal of Biomedical Imaging.

5. Can I use a manuscript in International Journal of Biomedical Imaging that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper International Journal of Biomedical Imaging that you can download at the end.

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7. Where can I find the template for the International Journal of Biomedical Imaging?

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8. Can I reformat my paper to fit the International Journal of Biomedical Imaging's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. International Journal of Biomedical Imaging an online tool or is there a desktop version?

SciSpace's International Journal of Biomedical Imaging is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

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After writing your paper autoformatting in International Journal of Biomedical Imaging, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is International Journal of Biomedical Imaging's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for International Journal of Biomedical Imaging?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for International Journal of Biomedical Imaging. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In International Journal of Biomedical Imaging?

The 5 most common citation types in order of usage for International Journal of Biomedical Imaging are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the International Journal of Biomedical Imaging?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per International Journal of Biomedical Imaging's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download International Journal of Biomedical Imaging in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in International Journal of Biomedical Imaging Endnote style according to Elsevier guidelines.

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