Comparison of signal to noise ratios from spatial and frequency domain formulations of nonprewhitening model observers in digital mammography

Magnetic Resonance Imaging under Image Enhancement Algorithm to Analyze the Clinical Value of Placement of Drainage Tube on Incision Healing after Hepatobiliary Surgery

This study was aimed at exploring the application value of magnetic resonance imaging (MRI) based on image enhancement algorithm in analyzing the placement of drainage tubes in the healing of incisions after hepatobiliary surgery. A total of 70 patients with liver cancer undergoing laparoscopic hepatobiliary surgery were selected, including 34 males and 36 females. According to the detection method of postoperative recovery, they were divided into a group A (conventional MRI detection) and a group B (MRI detection based on Retinex algorithm). Patients were divided into two groups according to whether subcutaneous drainage tubes were placed: group C (no subcutaneous drainage tubes were placed) and group D (subcutaneous drainage tubes were placed), with 35 patients in each group. The results showed that there was no significant difference between group A and group B in tumor residual or recurrence. The detection rate of tumor capsule in group B was significantly higher than that in group A (P < 0.05). The sensitivity, specificity, and accuracy of group A for the detection of recurrent lesions were 63.40%, 86.90%, and 78.60%, respectively; those in group B were 82.70%, 98.50%, and 93.20%, respectively. Therefore, the difference between the two groups was statistically significant (P < 0.05). The incidence of poor wound healing and infection in group C were significantly lower than those in group D (P < 0.05). Therefore, the effect of MRI detection based on image enhancement algorithm was more conducive to the evaluation of postoperative recovery due to the traditional MRI detection. In addition, the drainage tube was helpful to the postoperative wound healing and showed high clinical value.

Inverse Compton radiation: a novel x-ray source for K-edge subtraction angiography?

Coronary angiography is clinically used worldwide to diagnose diseases of coronary arteries. Despite its effectiveness, this technique is quite invasive and it is associated with significant risks due to the arterial catheterisation needed to inject the contrast agent. A valid alternative is using the K-edge subtraction (KES) method, which is based on the subtraction of two images acquired at energies bracketing the K-edge of the contrast element. The enhanced sensitivity of KES allows the intravenous injection of the contrast agent, thus reducing the risks of catheterisation. This technique can be effectively implemented by using intense and quasi-monochromatic x-ray beams. Synchrotron radiation has been proven to work well for this purpose, but its cost and size prevent a widespread clinical application. Inverse Compton sources are among the most promising innovative sources of intense and quasi-monochromatic x-rays. These sources are intrinsically more compact than those based on synchrotron radiation. In this work, the potential application of inverse Compton radiation to KES angiography is investigated. To this purpose, after a short review of the physics behind the inverse Compton process, an analytical framework is described. The proposed model is based on the application of the KES algorithm to calculate the SNR of details inside a suitable mathematical phantom. That allowed us to identify the characteristics of an inverse Compton source required for KES imaging. In particular, it was estimated that a photon fluence of 10⁸ ph mm^-2 is necessary to detect signals of clinical interest. Novel sources based on inverse Compton promise to achieve this requirement with an acquisition time of few hundreds of ms. This feature, together with compactness, broad two-dimensional radiation field, absence of harmonic contamination and the ability to deliver high photon fluxes also at high energies, makes this kind of sources promising for KES angiography and other diagnostic applications.

Toward image quality assessment in mammography using model observers: Detection of a calcification-like object

PURPOSE

Model observers (MOs) are of interest in the field of medical imaging to assess image quality. However, before procedures using MOs can be proposed in quality control guidelines for mammography systems, we need to know whether MOs are sensitive to changes in image quality and correlations in background structure. Therefore, as a proof of principle, in this study human and model observer (MO) performance are compared for the detection of calcification-like objects using different background structures and image quality levels of unprocessed mammography images.

METHOD

Three different phantoms, homogeneous polymethyl methacrylate, BR3D slabs with swirled patterns (CIRS, Norfolk, VA, USA), and a prototype anthropomorphic breast phantom (Institute of Medical Physics and Radiation Protection, Technische Hochschule Mittelhessen, Germany) were imaged on an Amulet Innovality (FujiFilm, Tokyo, Japan) mammographic X-ray unit. Because the complexities of the structures of these three phantoms were different and not optimized to match the characteristics of real mammographic images, image processing was not applied in this study. In addition, real mammograms were acquired on the same system. Regions of interest (ROIs) were extracted from each image. In half of the ROIs, a 0.25-mm diameter disk was inserted at four different contrast levels to represent a calcification-like object. Each ROI was then modified, so four image qualities relevant for mammography were simulated. The signal-present and signal-absent ROIs were evaluated by a non-pre-whitening model observer with eye filter (NPWE) and a channelized Hotelling observer (CHO) using dense difference of Gaussian channels. The ROIs were also evaluated by human observers in a two alternative forced choice experiment. Detectability results for the human and model observer experiments were correlated using a mixed-effect regression model. Threshold disk contrasts for human and predicted human observer performance based on the NPWE MO and CHO were estimated.

RESULTS

Global trends in threshold contrast were similar for the different background structures, but absolute contrast threshold levels differed. Contrast thresholds tended to be lower in ROIs from simple phantoms compared with ROIs from real mammographic images. The correlation between human and model observer performance was not affected by the range of image quality levels studied.

CONCLUSIONS

The correlation between human and model observer performance does not depend on image quality. This is a promising outcome for the use of model observers in image quality analysis and allows for subsequent research toward the development of MO-based quality control procedures and guidelines.