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Automatic left ventricle segmentation in volumetric SPECT data set by variational level set.

Mohammad Hosntalab¹, Farshid Babapour-Mofrad, Nazgol Monshizadeh

¹Faculty of Engineering, Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran. mhosntalab@yahoo.com

International Journal of Computer Assisted Radiology and Surgery

|June 15, 2012

Summary

A new variational level set method accurately automates left ventricle (LV) contour extraction in cardiac SPECT images. This technique improves LV quantification in nuclear medicine by providing smooth, precise borders, enhancing diagnostic capabilities.

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Published on: February 16, 2016

Area of Science:

Nuclear Medicine Imaging
Cardiovascular Imaging Analysis
Medical Image Segmentation

Background:

Left ventricle (LV) quantification in nuclear medicine, particularly myocardial perfusion scintigraphy, presents significant challenges.
Accurate LV border extraction is crucial for reliable ventriculography and diagnosis.
Existing methods often struggle with image noise and anatomical variations.

Purpose of the Study:

To develop and validate an automated method for left ventricle myocardial border extraction in SPECT datasets.
To improve the accuracy and efficiency of LV ventriculography in nuclear medicine.
To address the challenges of LV quantification in myocardial perfusion scintigraphy.

Main Methods:

Implementation of an automatic segmentation of the LV in volumetric SPECT data using a variational level set algorithm.
A two-step process involving initialization (adaptive thresholding, morphological operations) and segmentation (variational level set).
Evaluation by comparing automated contours with manually obtained boundaries in 10 SPECT datasets using ROC analysis.

Main Results:

The proposed variational level set method achieved high accuracy in segmenting LV regions.
Sensitivity and specificity for ventricular outline detection were reported as 88.9% and 96.8%, respectively.
The method demonstrated effectiveness and robustness in automatic LV contour extraction.

Conclusions:

A novel variational level set technique successfully automates LV contour tracing in cardiac SPECT data.
The method produces smooth and accurate LV contours, minimizing interference from adjacent structures.
This automated approach enhances LV quantification in nuclear medicine imaging.