An automatic segmentation method of a parameter-adaptive PCNN for medical images

An automatic segmentation method of a parameter-adaptive PCNN for medical images Int J CARS (2017) 12:1511–1519 DOI 10.1007/s11548-017-1597-2 ORIGINAL ARTICLE An automatic segmentation method of a parameter-adaptive PCNN for medical images 1 2 3 4 1 Jing Lian · Bin Shi · Mingcong Li · Ziwei Nan · Yide Ma Received: 10 January 2017 / Accepted: 24 April 2017 / Published online: 5 May 2017 © CARS 2017 Abstract Conclusion The algorithm has a great potential to achieve Purpose Since pre-processing and initial segmentation the pre-processing and initial segmentation steps in various steps in medical images directly affect the final segmentation medical images. This is a premise for assisting physicians to results of the regions of interesting, an automatic segmenta- detect and diagnose clinical cases. tion method of a parameter-adaptive pulse-coupled neural network is proposed to integrate the above-mentioned two Keywords Parameter-adaptive pulse-coupled neural segmentation steps into one. This method has a low compu- network · Image segmentation · Optimal histogram tational complexity for different kinds of medical images and threshold · Ultrasound image · Magnetic resonance image · has a high segmentation precision. Mammogram image Methods The method comprises four steps. Firstly, an opti- mal histogram threshold is used to determine the parameter Introduction α for different kinds of http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Computer Assisted Radiology and Surgery Springer Journals

An automatic segmentation method of a parameter-adaptive PCNN for medical images

Loading next page...
1
 
/lp/springer_journal/an-automatic-segmentation-method-of-a-parameter-adaptive-pcnn-for-jyYyKolBY0
Publisher
Springer International Publishing
Copyright
Copyright © 2017 by CARS
Subject
Medicine & Public Health; Imaging / Radiology; Surgery; Health Informatics; Computer Imaging, Vision, Pattern Recognition and Graphics; Computer Science, general
ISSN
1861-6410
eISSN
1861-6429
D.O.I.
10.1007/s11548-017-1597-2
Publisher site
See Article on Publisher Site

Abstract

Int J CARS (2017) 12:1511–1519 DOI 10.1007/s11548-017-1597-2 ORIGINAL ARTICLE An automatic segmentation method of a parameter-adaptive PCNN for medical images 1 2 3 4 1 Jing Lian · Bin Shi · Mingcong Li · Ziwei Nan · Yide Ma Received: 10 January 2017 / Accepted: 24 April 2017 / Published online: 5 May 2017 © CARS 2017 Abstract Conclusion The algorithm has a great potential to achieve Purpose Since pre-processing and initial segmentation the pre-processing and initial segmentation steps in various steps in medical images directly affect the final segmentation medical images. This is a premise for assisting physicians to results of the regions of interesting, an automatic segmenta- detect and diagnose clinical cases. tion method of a parameter-adaptive pulse-coupled neural network is proposed to integrate the above-mentioned two Keywords Parameter-adaptive pulse-coupled neural segmentation steps into one. This method has a low compu- network · Image segmentation · Optimal histogram tational complexity for different kinds of medical images and threshold · Ultrasound image · Magnetic resonance image · has a high segmentation precision. Mammogram image Methods The method comprises four steps. Firstly, an opti- mal histogram threshold is used to determine the parameter Introduction α for different kinds of

Journal

International Journal of Computer Assisted Radiology and SurgerySpringer Journals

Published: May 5, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off