Abstract
The objective of this study was to improve the visibility of anatomical details by applying off‐line postimage processing in chest computed radiography (CR). Four spatial domain‐based external image processing techniques were developed by using MATLAB software version 7.0.0.19920 (R14) and image processing tools. The developed techniques were implemented to sample images and their visual appearances confirmed by two consultant radiologists to be clinically adequate. The techniques were then applied to 200 chest clinical images and randomized with other 100 images previously processed online. These 300 images were presented to three experienced radiologists for image quality assessment using standard quality criteria. The mean and ranges of the average scores for three radiologists were characterized for each of the developed technique and imaging system. The Mann‐Whitney U‐test was used to test the difference of details visibility between the images processed using each of the developed techniques and the corresponding images processed using default algorithms. The results show that the visibility of anatomical features improved significantly (0.005≤p≤0.02) with combinations of intensity values adjustment and/or spatial linear filtering techniques for images acquired using 60≤kVp≤70. However, there was no improvement for images acquired using 102≤kVp≤107 (0.127≤p≤0.48). In conclusion, the use of external image processing for optimization can be effective in chest CR, but should be implemented in consultations with the radiologists.PACS number: 87.59.−e, 87.59.−B, 87.59.−bd
Highlights
323 Muhogora et al.: Off-line postimage processing in chest radiography algorithms, as reported by radiologists.[5,6] This has partly been attributed to low contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) properties, as well as the lack of knowledge on the implemented online image processing
It has been observed that, the low cost computed radiography (CR) system (LCCS) can display anatomical details comparably to conventional CR system (CCS), it is associated with higher patient dose by a factor of up to 2.5 for similar sized patients.[2]. In that study, the relative comparison between the two systems was done since the systems were being operated at similar high tube potentials
The improvement in image quality for these radiographs shows that the developed algorithms are efficient For high kVp radiographs, none of developed technique could be effective (Figs. 6 to 9, Tables 6 to 9), the significance level of which can be summarized as 0.127 ≤ p ≤ 0.48 for images acquired using 102 ≤ kVp ≤ 107
Summary
323 Muhogora et al.: Off-line postimage processing in chest radiography algorithms, as reported by radiologists.[5,6] This has partly been attributed to low CNR and SNR properties, as well as the lack of knowledge on the implemented online image processing. Since the results from the earlier study[2] had shown inadequate image quality with relatively higher average patient dose at high kVps, it was reasonably inferred that the image quality at low kVps could be inadequate This view motivated an attempt to improve the visibility of anatomical details by applying external postimage processing on chest computed radiographs acquired using both low and high kVps. The objective of this study was, to develop quantitative spatial domain-based external image processing techniques and evaluate their potentials for the improvement of anatomical visibility on studied low cost CR system
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