A multiresolution processing method for contrast enhancement in portal imaging

Abstract

Portal images have a unique feature among the imaging modalities used in radiotherapy: they provide direct visualization of the irradiated volumes. However, contrast and spatial resolution are strongly limited due to the high energy of the radiation sources. Because of this, imaging modalities using x-ray energy beams have gained importance in the verification of patient positioning, replacing portal imaging. The purpose of this work was to develop a method for the enhancement of local contrast in portal images. The method operates in the sub-bands of a wavelet decomposition of the image, re-scaling them in such a way that coefficients in the high and medium resolution sub-bands are amplified-an approach totally different from those operating on the image histogram, widely used nowadays. Portal images of an anthropomorphic phantom were acquired in an electronic portal imaging device. Then, different re-scaling strategies were investigated, studying the effects of the scaling parameters on the enhanced images. Also, the effect of using different types of transform was studied. Finally, the implemented methods were combined with histogram equalization methods like the contrast limited adaptive histogram equalization, and these combinations were compared. Uniform amplification of the detail sub-bands shows the best results in contrast enhancement. On the other hand, linear re-escalation of the high resolution sub-bands increases the visibility of fine detail in the images, at the expense of an increase in noise levels. Also, since processing is applied only to detail sub-bands, not to the approximation, the mean gray level of the image is minimally modified and no further display adjustments are required. It is shown that re-escalation of the detail sub-bands of portal images can be used as an efficient method for the enhancement of both the local contrast and the resolution of these images.

Electronic portal image enhancement based on nonuniformity correction in wavelet domain

“…As shown in Table 1, image quality measures have improved all processed images compared to the original one. Here, our method in EC analysis is slightly better than the performance of González‐López 34 and outperforms other approaches; however, there is a more distinct gain in improvement by the EME and EMEE metric. The EC values also indicate more sharped edges in our proposed method relative to the original image.…”

“…The EC values also indicate more sharped edges in our proposed method relative to the original image. Here, one of the main differences between our proposed method and González‐López 34 is that on which he worked high‐dose database (therefore, minimum noise level in the images); however, we implemented our method according to the existing low/high noise in high/low dose images. Moreover, we have performed the homomorphic filtering on the approximation sub‐band of wavelet decomposition either in low‐ or high‐dose datasets that improved our enhancement and reconstruction.…”

“…Afterward, our desired enhanced image is achieved by adding the weighted reconstructed image to the preprocessed image as expressed in Equation (). Because we worked on different dose levels (with different noise levels) in our database, unlike González‐López, 34 we therefore added this empirically added weight ($$w=2$$) for the enhanced image to have the same intensity level as the original image: $$\begin{equation} \text{Enhanced image} = w\cdot g(x,y) + f(x,y). \end{equation}$$…”

“…To conduct a comparative study, we also examined some approaches introduced in related works section, such as Ref. [34] in which the contrast enhancement of portal images is based on the amplification of image details merely through rescaling the detail sub-bands of the decomposed image in the wavelet domain or other methods, 21,23,26 which used CLAHE, ACE, and AHE (see Tables 1 and 2). The specifications of our experiment are as follows.…”

“…Qiu et al 33 proposed a processing chain, including a high-pass filter and a contrast-limited AHE filter, which optimizes processing parameters per disease case and imaging modality. González-López 34 proposed a straightforward local enhancement method for portal images. In his method, a multiresolution-processing algorithm was introduced for this purpose.…”