Identifying tissue types in MR images of the prostate

Philip Allen; Lynsey Hamlet; James Graham; Charles Hutchinson

Identifying tissue types in MR images of the prostate

Philip Allen, Lynsey Hamlet, James Graham, Charles Hutchinson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper we present an initial exploration of the use of image texture measures to distinguish glandular and stromal Benign Prostatic Hyperplasia (BPH). Using image entropy and grey-level granulometry we show that quantitative texture measures can be found that correspond to visual classification of images into “granular” and “smooth” appearance, which have previously been associated with these classes. Some texture measures also correspond with the ratio of the volumes of the prostate’s central gland and peripheral zone, which is also considered to be indicative of the severity of BPH.

Original language	English
Title of host publication	host publication
Editors	Majid Mirmehdi
Publisher	BMVA Press
Pages	71-74
Number of pages	4
ISBN (Print)	1 901725 28 6
Publication status	Published - Jul 2005
Event	Medical Image Understanding and Analysis - University of Bristol Duration: 19 Jul 2005 → 20 Jul 2005 http://www.miua.org.uk

Conference

Conference	Medical Image Understanding and Analysis
City	University of Bristol
Period	19/07/05 → 20/07/05
Internet address	http://www.miua.org.uk

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title = "Identifying tissue types in MR images of the prostate",

abstract = "In this paper we present an initial exploration of the use of image texture measures to distinguish glandular and stromal Benign Prostatic Hyperplasia (BPH). Using image entropy and grey-level granulometry we show that quantitative texture measures can be found that correspond to visual classification of images into “granular” and “smooth” appearance, which have previously been associated with these classes. Some texture measures also correspond with the ratio of the volumes of the prostate{\textquoteright}s central gland and peripheral zone, which is also considered to be indicative of the severity of BPH.",

author = "Philip Allen and Lynsey Hamlet and James Graham and Charles Hutchinson",

year = "2005",

month = jul,

language = "English",

isbn = "1 901725 28 6",

pages = "71--74",

editor = "Majid Mirmehdi",

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publisher = "BMVA Press",

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note = "Medical Image Understanding and Analysis ; Conference date: 19-07-2005 Through 20-07-2005",

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TY - GEN

T1 - Identifying tissue types in MR images of the prostate

AU - Allen, Philip

AU - Hamlet, Lynsey

AU - Graham, James

AU - Hutchinson, Charles

PY - 2005/7

Y1 - 2005/7

N2 - In this paper we present an initial exploration of the use of image texture measures to distinguish glandular and stromal Benign Prostatic Hyperplasia (BPH). Using image entropy and grey-level granulometry we show that quantitative texture measures can be found that correspond to visual classification of images into “granular” and “smooth” appearance, which have previously been associated with these classes. Some texture measures also correspond with the ratio of the volumes of the prostate’s central gland and peripheral zone, which is also considered to be indicative of the severity of BPH.

AB - In this paper we present an initial exploration of the use of image texture measures to distinguish glandular and stromal Benign Prostatic Hyperplasia (BPH). Using image entropy and grey-level granulometry we show that quantitative texture measures can be found that correspond to visual classification of images into “granular” and “smooth” appearance, which have previously been associated with these classes. Some texture measures also correspond with the ratio of the volumes of the prostate’s central gland and peripheral zone, which is also considered to be indicative of the severity of BPH.

M3 - Conference contribution

SN - 1 901725 28 6

SP - 71

EP - 74

BT - host publication

A2 - Mirmehdi, Majid

PB - BMVA Press

T2 - Medical Image Understanding and Analysis

Y2 - 19 July 2005 through 20 July 2005

ER -

Identifying tissue types in MR images of the prostate

Abstract

Conference

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