Quantitative assessment of liver fibrosis: a novel automated image analysis

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Quantitative assessment of liver fibrosis: a novel automated image analysis

method

Authors: Matalka, Ismail I.1; Al-Jarrah, M.2; Manasrah, Toqa M.2

Source: Liver International, Volume 26, Number 9, November 2006, pp.

1054-1064(11)

Publisher: Blackwell Publishing

Abstract:

Matalka II, Al-Jarrah OM, Manasrah TM. Quantitative assessment of liver

fibrosis: a novel automated image analysis method.

Liver International 2006: 26: 1054-1064.

© 2006 The Author. Journal compilation © 2006 Blackwell Munksgaard Abstract:

Background:

Semiquantitative staging of liver fibrosis is a highly subjective procedure

and may lead to an uncertainty in judgment regarding the degree of severity

and hence the progression of the disease. Aim:

In this work, we present an automated quantification system (AQS) for

evaluating the degree of severity of fibrosis in liver biopsies based on

Ishak et al.'s classification. Accordingly, liver fibrosis is classified

into six classes depending on its severity and progression. The described

system is of special value in accurately assessing the prognosis of chronic

liver disease. Methods:

In our method, we tried to approximate the architecture of the fibrosis in

the subject sample using texture features and shape representation of the

fibrosis structural expansion with an overall accuracy of about 98%. Results

and conclusion:

The presented AQS is considered to be a novel approach in the domain of

automatic liver fibrosis quantification. It is a true quantification and

intelligent approach that attempts to utilize the current semiquantitative

methods of liver fibrosis assessment to turn them into real quantitative

ones with significant reduction in variability and subjectivity. We propose

that our method can be adopted by a panel of expert liver pathologists and

software to be developed and used on a wide scale.

Keywords: automatic quantification; Ishak scoring; liver fibrosis; neural

networks

Document Type: Research article

DOI: 10.1111/j.1478-3231.2006.01341.x

Affiliations: 1: Pathology and 2: Computer Engineering, Jordan University of

Science & Technology, Irbid, Jordan

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[Guest guest]

Quantitative assessment of liver fibrosis: a novel automated image analysis

method

Authors: Matalka, Ismail I.1; Al-Jarrah, M.2; Manasrah, Toqa M.2

Source: Liver International, Volume 26, Number 9, November 2006, pp.

1054-1064(11)

Publisher: Blackwell Publishing

Abstract:

Matalka II, Al-Jarrah OM, Manasrah TM. Quantitative assessment of liver

fibrosis: a novel automated image analysis method.

Liver International 2006: 26: 1054-1064.

© 2006 The Author. Journal compilation © 2006 Blackwell Munksgaard Abstract:

Background:

Semiquantitative staging of liver fibrosis is a highly subjective procedure

and may lead to an uncertainty in judgment regarding the degree of severity

and hence the progression of the disease. Aim:

In this work, we present an automated quantification system (AQS) for

evaluating the degree of severity of fibrosis in liver biopsies based on

Ishak et al.'s classification. Accordingly, liver fibrosis is classified

into six classes depending on its severity and progression. The described

system is of special value in accurately assessing the prognosis of chronic

liver disease. Methods:

In our method, we tried to approximate the architecture of the fibrosis in

the subject sample using texture features and shape representation of the

fibrosis structural expansion with an overall accuracy of about 98%. Results

and conclusion:

The presented AQS is considered to be a novel approach in the domain of

automatic liver fibrosis quantification. It is a true quantification and

intelligent approach that attempts to utilize the current semiquantitative

methods of liver fibrosis assessment to turn them into real quantitative

ones with significant reduction in variability and subjectivity. We propose

that our method can be adopted by a panel of expert liver pathologists and

software to be developed and used on a wide scale.

Keywords: automatic quantification; Ishak scoring; liver fibrosis; neural

networks

Document Type: Research article

DOI: 10.1111/j.1478-3231.2006.01341.x

Affiliations: 1: Pathology and 2: Computer Engineering, Jordan University of

Science & Technology, Irbid, Jordan

_________________________________________________________________

Add a contact to Windows Live Messenger for a chance to win a free

trip!

http://www.imagine-windowslive.com/minisites//default.aspx?locale=en-us & hmt\

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