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Technical Note: Image filtering to make computer-aided detection robust to image reconstruction kernel choice in lung
Masaki Ohkubo1, Akihiro Narita1, Shinichi Wada1
1Graduate School of Health Sciences, Niigata University, Niigata 951-8518, Japan.
Medical Physics
|July 3, 2016
Summary
A new MTFratio filtering method reduces computer-aided detection (CAD) system dependence on lung cancer CT screening reconstruction kernels. This filtering technique improves CAD performance by creating images similar to standard reconstruction kernels.
Area of Science:
- Radiology
- Medical Imaging
- Image Processing
Background:
- Computer-aided detection (CAD) system performance in lung cancer CT screening is sensitive to image reconstruction kernel choice.
- Reducing this kernel dependence is crucial for consistent CAD accuracy.
Purpose of the Study:
- To introduce and evaluate a novel image filtering method, MTFratio filtering, to minimize reconstruction kernel dependence in CT screening CAD.
- To assess the effectiveness of MTFratio filtering in improving CAD performance by making images reconstructed with different kernels comparable.
Main Methods:
- MTFratio filtering was developed using the ratio of modulation transfer functions (MTFs) of two kernels (fSTD and fSHARP) in the spatial-frequency domain.
- The method was applied to fSHARP reconstructed images to emulate fSTD images, with comparisons to mean and median filters.
- All image types were processed using a prototype CAD system for performance evaluation.
Main Results:
- MTFratio filtered images demonstrated high agreement with fSTD images (standard deviation ~6.0 HU).
- Mean and median filters produced significantly larger differences (~48.1 HU and ~57.9 HU, respectively).
- MTFratio filtering restored CAD performance on fSHARP images to levels equivalent to fSTD images, unlike mean or median filters.
Conclusions:
- The study validates the accuracy and effectiveness of MTFratio image filtering.
- MTFratio filtering successfully reduces the impact of reconstruction kernel selection on CAD system performance in lung cancer CT screening.
