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BLACK-BOUNDARY ARTIFACT GUIDED ABDOMINAL ORGAN SEGMENTATION

IP.com Disclosure Number: IPCOM000214484D
Publication Date: 2012-Jan-31
Document File: 6 page(s) / 280K

Publishing Venue

The IP.com Prior Art Database

Abstract

The present invention is segmentation algorithm that provides contour of an organ surrounded by fat by using the black boundary artifact. The black boundary artifact simplifies image processing effort, as filters are required to be designed only to match the step–down edge valley profile. Further, the segmentation algorithm provides a higher probability for detecting correct organ-edge as there are no diffuse boundaries to be dealt with.

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BLACK-BOUNDARY ARTIFACT GUIDED ABDOMINAL ORGAN SEGMENTATION

BRIEF ABSTRACT

The present invention is segmentation algorithm that provides contour of an organ surrounded by fat by using the black boundary artifact.  The black boundary artifact simplifies image processing effort, as filters are required to be designed only to match the step–down edge valley profile.  Further, the segmentation algorithm provides a higher probability for detecting correct organ-edge as there are no diffuse boundaries to be dealt with.

KEYWORDS

Liver segmentation, adipose tissue, abdominal cavity, segmentation algorithms, black-boundary artifact, FIESTA, LAVA, MRI, magnetic resonance, liver contour

 

DETAILED DESCRIPTION

MRI imaging is a useful abdominal imaging technique that is being widely studied and becoming valuable means for abdominal organ investigation. Automatic diagnosis of liver pathologies has seen a significant advancement due to improved processing of MRI images. The first and fundamental step in all these investigative and diagnostic studies is liver segmentation.

A problem associated with segmentation of MRI liver images acquired using standard magnetic resonance (MR) clinical protocols such as LAVA is the absence of clear demarcating boundary around the periphery of liver.

Several conventional segmentation algorithms exist. Generally, conventional segmentation algorithms obtain liver contour from post-processing schemes applied to MRI acquisition data. Further, conventional liver segmentation algorithms are tailored to contrast present in the images acquired for clinical use and therefore need to be varied according to the clinical protocol being run on the MR scanner.  

Hence there is a need for an improved liver segmentation algorithm decoupled from protocol used for clinical scan and provides a more accurate estimate of liver contour.

Most abdominal organs, such as, liver and kidneys are surrounded by a layer of fat. This surrounding layer of fat can be used as the demarcating feature for identifying boundary of the abdominal organs, provided the fat can be highlighted in an image.

For a gradient echo (GRE) sequence or steady-state free precision based sequence, such as Fast Imaging Employing Steady-state Acquisition (FIESTA), TrueFISP and Balanced Fast Field Echo (b-FFE), a cancellation of intra-voxel water and fat signal occurs at the boundary of the liver, if the echo times (TE) of the sequence are appropriately selected. This cancellation typically manifests as a black boundary and is referred to as black-boundary artifact. A segmentation algorithm that uses chemical signatures of the anatomy, such as fat surrounding an organ, to guide MR data acquisition and provides segmentation tailored MRI dataset. The segmentation algorithm uses the black-boundary artifact to guide segmentation of the abdominal organs.

The black boundary simplifies...