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Selected aspects of corneal endothelial segmentation quality

Piorkowski A., Nurzynska K., Boldak C., Reska D., Gronkowska-Serafin J.

Journal of Medical Informatics & Technologies

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2015

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Vol. 24

155--163

EN

The number and shape of cells in endothelium layer is highly correlated with the quality of vision. Therefore, its precise and automatic description plays an important role in medicine. This work presents several aspects of image processing of endothelium layer acquired by specular microscope. The comparison of cell selection accuracy is discussed using two different approaches to solve this problem: convolution filtering methods, and snake-based method. Moreover, for verification results generated by dedicated software, supplied with the microscope, were utilized. Next, the precise segmentation method is applied to improve the segmentation. The results are inspected visually, but also CV, H, and CVSL parameters, used in medicine, are calculated. The research concludes that general visual outcomes achieved by all segmentation approaches give similar results, however deep insight into cell outline position reveals some differences, which were partially removed after precise segmentation application. The analysis of parameter values show high stability of CV and CVSL parameters.

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MESA: Complete approach for design and evaluation of segmentation methods using real and simulated tomographic images

Reska D., Jurczuk K., Boldak C., Kretowski M.

Biocybernetics and Biomedical Engineering

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2014

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Vol. 34, no. 3

146--158

EN

In this paper we present MESA: a platform for design and evaluation of medical image segmentation methods. The platform offers a complete approach for the method creation and validation using simulated and real tomographic images. The system consists of several modules that provide a comprehensive workflow for generation of test data, segmentation method development as well as experiment planning and execution. The test data can be created as a virtual scene that provides an ideal reference segmentation and is also used to simulate the input images by a virtual magnetic resonance imaging (MRI) scanner. Both ideal reference segmentation and simulated images could be utilized during the evaluation of the segmentation methods. The platform offers various experimental capabilities to measure and compare the performance of the methods on various data sets, parameters and initializations. The segmentation framework, currently based on deformable models, uses a template solution for dynamical composition and creation of two- and three-dimensional methods. The platform is based on a client–server architecture, with computational and data storage modules deployed on the server and with browser-based client applications. We demonstrate the platform capabilities during the design of segmentation methods with the use of simulated and actual tomographic images.

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Fast 3D Segmentation of Hepatic Images Combining Region and Boundary Criteria

Reska D., Boldak C, Kretowski M

Image Processing & Communications

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2012

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Vol. 17, no. 4

31--38

EN

A new approach to the liver segmentation from 3D images is presented and compared to the existing methods in terms of quality and speed of segmentation. The proposed technique is based on 3D deformable model (active surface) combining boundary and region information. The segmentation quality is comparable to the existing methods but the proposed technique is significantly faster. The experimental evaluation was performed on clinical datasets (both MRI and CT), representing typical as well as more challenging to segment liver shapes.