Automatic slice thickness measurement on three types of Catphan CT phantoms

Abstract

Objective: To develop an algorithm to measure slice thickness to run on three types of Catphan phantoms with the ability to adapt to any misalignment and rotation of the phantoms.
Method: Images of Catphan 500, 504, and 604 phantoms were examined. In addition, images with various slice thicknesses ranging from 1.5 to 10.0 mm, distance to the iso-center and phantom rotations were also examined. The automatic slice thickness algorithm was carried out by processing only objects within a circle having a diameter half that of the phantom diameter. A segmentation was performed within an inner circle with dynamic thresholds to produce binary images with wire and bead objects. Region properties were used to distinguish wire ramps and bead objects. At each identified wire ramp, the angle was detected using the Hough transform. Profile lines were then placed on each ramp based on the centroid coordinates and detected angles, and the full-width at half maximum (FWHM) determined for the average pixel profile. The slice thickness was obtained by multiplying the FWHM by the tangent of the ramp angle (23o). 
Results: Automatic measurements work well and have only a small difference (<0.5 mm) from manual measurements. For variations of slice thickness, automatic measurement successfully performs segmentation and correctly locates the profile line on all wire ramps. The results show values that are close (< 3mm) to the nominal thickness on thin slices, but less close for thicker slices. There is a strong correlation (R2 = 0.873) between automatic and manual measurements. Testing the algorithm at various distances from the iso-center and phantom rotation angle also produced accurate results. 
Conclusion: An automated algorithm for measuring slice thickness on three types of Catphan CT phantom images has been developed. The algorithm works well on various thicknesses, distances from the iso-center, and phantom rotations.

A challenge and solution for automatic thin slice thickness measurements on images of the Catphan phantom

“…The Catphan ® 500 phantom consists of four modules, i.e., CTP401, CTP528, CTP515, and CTP486. The CTP401 module containing four wire ramps with an angle of 23°was the only module used in this study [32]. One pair of wire ramps is oriented parallel to the x-axis, and the other pair to the y-axis.…”

“…One pair of wire ramps is oriented parallel to the x-axis, and the other pair to the y-axis. Apart from measuring slice thickness, wire ramps can also be used to measure z mis-alignment [32]. However, this study focuses on measuring thin slice thickness.…”

“…A previous study [31] had proposed a method to automatically measure slice thickness using three types of Catphan phantoms. The Hough transform was used [32] to detect the slight angle of the phantom's orientation in slice thickness measurements which commonly occurs. The use of the Hough transform for angle detection is quite accurate for relatively wide slice thicknesses, since the wire object is depicted as a long line in the axial image.…”

Automatic slice thickness measurement on computed tomography images of American College of Radiology phantom

“…This automatic method can be accessed by clicking the "calculate" button. Similar to previous studies [13], [23], for many images coming from different datasets, this method can be replicated easily as the input parameters can be customized according to the user's needs. The results obtained are also clearly displayed in the results column.…”

“…Good image quality can provide relevant information to help medical personnel to provide accurate diagnostic results to patients [12]. Because slice thickness has a direct impact on noise level [13] and image spatial resolution [14], it is one main parameter that determines image quality [13]. Thin slices are usually used for the examination of small organs or anomalies because they provide a  ISSN: 2252-8814 Int J Adv Appl Sci, Vol.…”