Automatic segmentation of ultrasonic image

S. H. Wong; K. L. Chan; P. W. Fung

doi:10.1109/TENCON.1993.320160

Automatic segmentation of ultrasonic image

S. H. Wong, K. L. Chan, P. W. Fung

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

3 Citations (Scopus)

Abstract

Automatic segmentation of ultrasonic images is a crucial step for their automatic morphological analysis. The ultrasonic images currently generated in the clinical environment provide significant contributions to the diagnosis of human tissues. Based on the ultrasonic appearance of tissue, the radiologists can carry out tissue identification by extracting and analyzing the visual information in the image. However, ultrasonic images are usually displayed in gray scale and exhibit many artifacts such as coarse resolution, low contrast and high noise. Interpretation of the ultrasonic image by human eye becomes more difficult and hence error-prone. Consequently, the difficulties are found to be solved by using statistical texture measure on the ultrasonic image.

Original language	English
Title of host publication	Proceedings Tencon '93: 1993 IEEE Region 10 Conference on "Computer, Communication, Control and Power Engineering"
Publisher	IEEE
Pages	910-913
Volume	2
ISBN (Print)	0780312333
DOIs	https://doi.org/10.1109/TENCON.1993.320160
Publication status	Published - Oct 1993
Event	1993 IEEE Region 10 Conference on Computer, Communication, Control and Power Engineering (TENCON '93) - Beijing, China Duration: 19 Oct 1993 → 21 Oct 1993

Conference

Conference	1993 IEEE Region 10 Conference on Computer, Communication, Control and Power Engineering (TENCON '93)
Place	China
City	Beijing
Period	19/10/93 → 21/10/93

Access Output

10.1109/TENCON.1993.320160

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@inproceedings{4208ffc07a004912b5bf326bc488467f,

title = "Automatic segmentation of ultrasonic image",

abstract = "Automatic segmentation of ultrasonic images is a crucial step for their automatic morphological analysis. The ultrasonic images currently generated in the clinical environment provide significant contributions to the diagnosis of human tissues. Based on the ultrasonic appearance of tissue, the radiologists can carry out tissue identification by extracting and analyzing the visual information in the image. However, ultrasonic images are usually displayed in gray scale and exhibit many artifacts such as coarse resolution, low contrast and high noise. Interpretation of the ultrasonic image by human eye becomes more difficult and hence error-prone. Consequently, the difficulties are found to be solved by using statistical texture measure on the ultrasonic image.",

author = "Wong, {S. H.} and Chan, {K. L.} and Fung, {P. W.}",

year = "1993",

month = oct,

doi = "10.1109/TENCON.1993.320160",

language = "English",

isbn = "0780312333",

volume = "2",

pages = "910--913",

booktitle = "Proceedings Tencon '93: 1993 IEEE Region 10 Conference on {"}Computer, Communication, Control and Power Engineering{"}",

publisher = "IEEE",

address = "United States",

note = "1993 IEEE Region 10 Conference on Computer, Communication, Control and Power Engineering (TENCON '93) ; Conference date: 19-10-1993 Through 21-10-1993",

}

Wong, SH, Chan, KL & Fung, PW 1993, Automatic segmentation of ultrasonic image. in Proceedings Tencon '93: 1993 IEEE Region 10 Conference on "Computer, Communication, Control and Power Engineering". vol. 2, IEEE, pp. 910-913, 1993 IEEE Region 10 Conference on Computer, Communication, Control and Power Engineering (TENCON '93), Beijing, China, 19/10/93. https://doi.org/10.1109/TENCON.1993.320160

Automatic segmentation of ultrasonic image. / Wong, S. H.; Chan, K. L.; Fung, P. W.
Proceedings Tencon '93: 1993 IEEE Region 10 Conference on "Computer, Communication, Control and Power Engineering". Vol. 2 IEEE, 1993. p. 910-913.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Automatic segmentation of ultrasonic image

AU - Wong, S. H.

AU - Chan, K. L.

AU - Fung, P. W.

PY - 1993/10

Y1 - 1993/10

N2 - Automatic segmentation of ultrasonic images is a crucial step for their automatic morphological analysis. The ultrasonic images currently generated in the clinical environment provide significant contributions to the diagnosis of human tissues. Based on the ultrasonic appearance of tissue, the radiologists can carry out tissue identification by extracting and analyzing the visual information in the image. However, ultrasonic images are usually displayed in gray scale and exhibit many artifacts such as coarse resolution, low contrast and high noise. Interpretation of the ultrasonic image by human eye becomes more difficult and hence error-prone. Consequently, the difficulties are found to be solved by using statistical texture measure on the ultrasonic image.

AB - Automatic segmentation of ultrasonic images is a crucial step for their automatic morphological analysis. The ultrasonic images currently generated in the clinical environment provide significant contributions to the diagnosis of human tissues. Based on the ultrasonic appearance of tissue, the radiologists can carry out tissue identification by extracting and analyzing the visual information in the image. However, ultrasonic images are usually displayed in gray scale and exhibit many artifacts such as coarse resolution, low contrast and high noise. Interpretation of the ultrasonic image by human eye becomes more difficult and hence error-prone. Consequently, the difficulties are found to be solved by using statistical texture measure on the ultrasonic image.

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0027711524&origin=recordpage

UR - http://www.scopus.com/inward/record.url?scp=0027711524&partnerID=8YFLogxK

U2 - 10.1109/TENCON.1993.320160

DO - 10.1109/TENCON.1993.320160

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0780312333

VL - 2

SP - 910

EP - 913

BT - Proceedings Tencon '93: 1993 IEEE Region 10 Conference on "Computer, Communication, Control and Power Engineering"

PB - IEEE

T2 - 1993 IEEE Region 10 Conference on Computer, Communication, Control and Power Engineering (TENCON '93)

Y2 - 19 October 1993 through 21 October 1993

ER -

Automatic segmentation of ultrasonic image

Abstract

Conference

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this