A fractional-order edge detection operator for medical image structure feature extraction

This paper introduces a novel fractional-order gradient operator for medical image structure feature extraction. The proposed operator can be seen as generalization of the first-order Sobel operator based on the GL fractional derivative definition. The generalization goal is to utilize the frequency...

Full description

Saved in:
Bibliographic Details
Main Authors: Dan Tian, Jingfei Wu, Yajie Yang
Format: Conference Proceeding
Language:English
Subjects:
Feature extraction
Fractional-order
Image edge detection
Medical diagnostic imaging
Medical Image
Noise
Sobel Detection
Thresholding Selection
Ultrasonic imaging
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 5176
container_issue
container_start_page 5173
container_title
container_volume
creator Dan Tian
Jingfei Wu
Yajie Yang
description This paper introduces a novel fractional-order gradient operator for medical image structure feature extraction. The proposed operator can be seen as generalization of the first-order Sobel operator based on the GL fractional derivative definition. The generalization goal is to utilize the frequency characteristic of the fractional derivative for extracting more structure feature details. A thresholding is set based on the average fractional-order gradient for marking the edge points, and then the image structure can be extracted. Experiments show that the proposed fractional-order operator yields good visual effects.
doi_str_mv 10.1109/CCDC.2014.6853103
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_6853103</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6853103</ieee_id><sourcerecordid>6853103</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-3b4821c0d6e79bad1fcc796e4c1eb0dea60547b2e962225ac96a168b50c3b303</originalsourceid><addsrcrecordid>eNo9UEtqwzAUVH_QJM0BSje6gN33JFmylsH9QqCbLNpVkKXn4uLUQVagvX1N6nYxDMwMwzCMXSPkiGBvq-quygWgynVZSAR5wpbWlKiMtdKA1qdshlaVmVXKnLH5n2Fez_8NaS_ZfBg-YIxLgBl7W_EmOp_a_tN1WR8DRU7hnXigREeZ93uKLvWRNyN2FFrvOt7u3BgaUjz4dIjEG3JHpq801V2xi8Z1Ay0nXrDNw_2mesrWL4_P1WqdtWiKlMlalQI9BE3G1i5g472xmpRHqiGQ01AoUwuyWghROG-1Q13WBXhZS5ALdvNb2xLRdh_HYfF7Oz0kfwDyoldy</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>A fractional-order edge detection operator for medical image structure feature extraction</title><source>IEEE Xplore All Conference Series</source><creator>Dan Tian ; Jingfei Wu ; Yajie Yang</creator><creatorcontrib>Dan Tian ; Jingfei Wu ; Yajie Yang</creatorcontrib><description>This paper introduces a novel fractional-order gradient operator for medical image structure feature extraction. The proposed operator can be seen as generalization of the first-order Sobel operator based on the GL fractional derivative definition. The generalization goal is to utilize the frequency characteristic of the fractional derivative for extracting more structure feature details. A thresholding is set based on the average fractional-order gradient for marking the edge points, and then the image structure can be extracted. Experiments show that the proposed fractional-order operator yields good visual effects.</description><identifier>ISSN: 1948-9439</identifier><identifier>ISBN: 147993707X</identifier><identifier>ISBN: 9781479937073</identifier><identifier>EISSN: 1948-9447</identifier><identifier>EISBN: 9781479937066</identifier><identifier>EISBN: 9781479937080</identifier><identifier>EISBN: 1479937088</identifier><identifier>EISBN: 1479937061</identifier><identifier>DOI: 10.1109/CCDC.2014.6853103</identifier><language>eng</language><publisher>IEEE</publisher><subject>Feature extraction ; Fractional-order ; Image edge detection ; Medical diagnostic imaging ; Medical Image ; Noise ; Sobel Detection ; Thresholding Selection ; Ultrasonic imaging</subject><ispartof>The 26th Chinese Control and Decision Conference (2014 CCDC), 2014, p.5173-5176</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6853103$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6853103$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Dan Tian</creatorcontrib><creatorcontrib>Jingfei Wu</creatorcontrib><creatorcontrib>Yajie Yang</creatorcontrib><title>A fractional-order edge detection operator for medical image structure feature extraction</title><title>The 26th Chinese Control and Decision Conference (2014 CCDC)</title><addtitle>CCDC</addtitle><description>This paper introduces a novel fractional-order gradient operator for medical image structure feature extraction. The proposed operator can be seen as generalization of the first-order Sobel operator based on the GL fractional derivative definition. The generalization goal is to utilize the frequency characteristic of the fractional derivative for extracting more structure feature details. A thresholding is set based on the average fractional-order gradient for marking the edge points, and then the image structure can be extracted. Experiments show that the proposed fractional-order operator yields good visual effects.</description><subject>Feature extraction</subject><subject>Fractional-order</subject><subject>Image edge detection</subject><subject>Medical diagnostic imaging</subject><subject>Medical Image</subject><subject>Noise</subject><subject>Sobel Detection</subject><subject>Thresholding Selection</subject><subject>Ultrasonic imaging</subject><issn>1948-9439</issn><issn>1948-9447</issn><isbn>147993707X</isbn><isbn>9781479937073</isbn><isbn>9781479937066</isbn><isbn>9781479937080</isbn><isbn>1479937088</isbn><isbn>1479937061</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2014</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo9UEtqwzAUVH_QJM0BSje6gN33JFmylsH9QqCbLNpVkKXn4uLUQVagvX1N6nYxDMwMwzCMXSPkiGBvq-quygWgynVZSAR5wpbWlKiMtdKA1qdshlaVmVXKnLH5n2Fez_8NaS_ZfBg-YIxLgBl7W_EmOp_a_tN1WR8DRU7hnXigREeZ93uKLvWRNyN2FFrvOt7u3BgaUjz4dIjEG3JHpq801V2xi8Z1Ay0nXrDNw_2mesrWL4_P1WqdtWiKlMlalQI9BE3G1i5g472xmpRHqiGQ01AoUwuyWghROG-1Q13WBXhZS5ALdvNb2xLRdh_HYfF7Oz0kfwDyoldy</recordid><startdate>201405</startdate><enddate>201405</enddate><creator>Dan Tian</creator><creator>Jingfei Wu</creator><creator>Yajie Yang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201405</creationdate><title>A fractional-order edge detection operator for medical image structure feature extraction</title><author>Dan Tian ; Jingfei Wu ; Yajie Yang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-3b4821c0d6e79bad1fcc796e4c1eb0dea60547b2e962225ac96a168b50c3b303</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Feature extraction</topic><topic>Fractional-order</topic><topic>Image edge detection</topic><topic>Medical diagnostic imaging</topic><topic>Medical Image</topic><topic>Noise</topic><topic>Sobel Detection</topic><topic>Thresholding Selection</topic><topic>Ultrasonic imaging</topic><toplevel>online_resources</toplevel><creatorcontrib>Dan Tian</creatorcontrib><creatorcontrib>Jingfei Wu</creatorcontrib><creatorcontrib>Yajie Yang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dan Tian</au><au>Jingfei Wu</au><au>Yajie Yang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A fractional-order edge detection operator for medical image structure feature extraction</atitle><btitle>The 26th Chinese Control and Decision Conference (2014 CCDC)</btitle><stitle>CCDC</stitle><date>2014-05</date><risdate>2014</risdate><spage>5173</spage><epage>5176</epage><pages>5173-5176</pages><issn>1948-9439</issn><eissn>1948-9447</eissn><isbn>147993707X</isbn><isbn>9781479937073</isbn><eisbn>9781479937066</eisbn><eisbn>9781479937080</eisbn><eisbn>1479937088</eisbn><eisbn>1479937061</eisbn><abstract>This paper introduces a novel fractional-order gradient operator for medical image structure feature extraction. The proposed operator can be seen as generalization of the first-order Sobel operator based on the GL fractional derivative definition. The generalization goal is to utilize the frequency characteristic of the fractional derivative for extracting more structure feature details. A thresholding is set based on the average fractional-order gradient for marking the edge points, and then the image structure can be extracted. Experiments show that the proposed fractional-order operator yields good visual effects.</abstract><pub>IEEE</pub><doi>10.1109/CCDC.2014.6853103</doi><tpages>4</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1948-9439
ispartof The 26th Chinese Control and Decision Conference (2014 CCDC), 2014, p.5173-5176
issn 1948-9439
1948-9447
language eng
recordid cdi_ieee_primary_6853103
source IEEE Xplore All Conference Series
subjects Feature extraction
Fractional-order
Image edge detection
Medical diagnostic imaging
Medical Image
Noise
Sobel Detection
Thresholding Selection
Ultrasonic imaging
title A fractional-order edge detection operator for medical image structure feature extraction
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T19%3A13%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=A%20fractional-order%20edge%20detection%20operator%20for%20medical%20image%20structure%20feature%20extraction&rft.btitle=The%2026th%20Chinese%20Control%20and%20Decision%20Conference%20(2014%20CCDC)&rft.au=Dan%20Tian&rft.date=2014-05&rft.spage=5173&rft.epage=5176&rft.pages=5173-5176&rft.issn=1948-9439&rft.eissn=1948-9447&rft.isbn=147993707X&rft.isbn_list=9781479937073&rft_id=info:doi/10.1109/CCDC.2014.6853103&rft.eisbn=9781479937066&rft.eisbn_list=9781479937080&rft.eisbn_list=1479937088&rft.eisbn_list=1479937061&rft_dat=%3Cieee_CHZPO%3E6853103%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i175t-3b4821c0d6e79bad1fcc796e4c1eb0dea60547b2e962225ac96a168b50c3b303%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6853103&rfr_iscdi=true