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Immediate verification of whether a patient being examined is correct is desirable, even if the scan ranges change during different examinations for the same patient. This study proposes an advanced biological fingerprint technique for the rapid and reliable verification of various scan ranges in computed tomography (CT) scans of the torso of the same patient. The method comprises the following steps: geometric correction of different scans, local feature extraction, mismatch elimination, and similarity evaluation. The geometric magnification correction was aligned at the scanner table height in the first two steps, and the local maxima were calculated as the local features. In the third step, local features from the follow-up scout image are matched to those in the corresponding baseline scout image via template matching and outlier elimination via a robust estimator. We evaluated the correspondence rate based on the inlier ratio between corresponding scout images. The ratio of inliers between the baseline and follow-up scout images was assessed as the similarity score. The clinical dataset, including chest, abdomen-pelvis, and chest-abdomen-pelvis scans, included 600 patients (372 men, 68 ± 12 years) who underwent two routine torso CT examinations. The highest area under the receiver operating characteristic curve (AUC) was 0.996, which was sufficient for patient verification. Moreover, the verification results were comparable to the conventional method, which uses scout images in the same scan range. Patient identity verification was achieved before the main scan, even in follow-up torso CT, under different scan ranges., (© 2022. The Author(s), under exclusive licence to Japanese Society of Radiological Technology and Japan Society of Medical Physics.)

To determine the optimal display conditions for ultra-high-resolution computed tomography (UHRCT) images in clinical practice, this study investigated the effects of liquid-crystal display (LCD) resolution and displayed image size on the spatial resolution of phantom images acquired using a UHRCT system. A phantom designed to evaluate the high-contrast resolution was scanned. The scan data were reconstructed into four types of UHRCT image series consisting of the following possible combinations: two types of reconstruction kernels on the filtered back-projection method (for the lung and mediastinum) and two types of matrix sizes (1024 2 and 2048 2 ). These images were displayed under eight types of display conditions: three image sizes displayed on a 2-megapixel (MP) and 3-MP color LCD and two image sizes on an 8-MP color LCD. A total of 32 samples (four image series × eight display conditions) were evaluated by eight observers for high-contrast resolution. The high-contrast resolution of the displayed UHRCT images was significantly affected by the displayed image size, although the largest (full-screen) displayed image size did not necessarily show the maximum high-contrast resolution. When the images were displayed in the full-screen size, LCD resolution affected the high-contrast resolution of only the 2048 2 -matrix-size images reconstructed using the lung kernel. In conclusion, the spatial resolution of UHRCT images may be affected by LCD resolution and displayed image size. To optimize the clinical display conditions for UHRCT images, it is necessary to adopt an LCD with an adequate resolution for each viewing situation., (© 2022. The Author(s), under exclusive licence to Japanese Society of Radiological Technology and Japan Society of Medical Physics.)

This paper outlines the history of biometrics for personal identification, the current status of the initial biological fingerprint techniques for digital chest radiography, and patient verification during medical imaging, such as computed tomography and magnetic resonance imaging. Automated image recognition and identification developed for clinical images without metadata could also be applied to the identification of victims in mass disasters or other unidentified individuals. The development of methods that are adaptive to a wide range of recent imaging modalities in the fields of radiologic technology, patient safety, forensic pathology, and forensic odontology is still in its early stages. However, its importance in practice will continue to increase in the future.

Information on medical devices embedded in the body is important in the identification of an unidentified body. Computed tomography (CT) is a powerful imaging modality; however, metallic artifacts deteriorate the image quality because of the reconstruction method. On the contrary, CT scout view is less affected by metallic artifacts compared to CT. It is a simple method to classify the body into three rough parts for postmortem CT (PMCT) scout view, and an algorithm used to detect the location of the implanted metal has been developed for personal identification in forensic pathology. Of the test images, 97% were correctly classified into the three body parts. The true-positive rate for detection of the implanted metal in the scout view was 96.5%. Therefore, our simple methods are applicable in PMCT scout views and would be particularly useful for forensic pathology.

We aimed to evaluate the identification performance achieved using biological fingerprints extracted from averaged chest radiographs and template-matching techniques for the prevention of left-right flipping mistakes. We produced averaged chest radiographs for each sex by averaging 100 posteroanterior chest radiographs. Further, 400 and 566 chest radiographs were used in consistency and validation tests, respectively, and they were flipped horizontally to produce flipped chest radiographs under the assumption that the left-right flipping mistake occurred. The correlation values obtained with chest radiographs and those obtained with flipped chest radiographs were calculated. When we used correlation indices calculated from the correlation values from four biological fingerprints except for the lung apex, 96.5% (386/400) and 95.8% (542/566) of the left or right sides were identified correctly in the consistency and validation tests, respectively. This result indicates that our proposed method would be promising for the prevention of left-right flipping mistakes.

The temporal subtraction (TS) technique requires the same patient's chest radiographs (CXRs) acquired on different dates, whereas the similar subtraction (SS) technique can be used in patients who have no previous CXR, using similar CXRs from different patients. This study aimed to examine the depiction ability of SS images with simulated nodules in comparison with that of TS images with 2- and 7-year acquisition intervals. One hundred patients were randomly selected from our image database. The most recently acquired images of the patients were used as target images for subtraction. The simulated nodule was superimposed on each target image to examine the usefulness of the SS technique. The most (Top 1) and ten most (Top 10) similar images for each target image were identified in the 24,254-image database using a template-matching technique, and used for the SS technique. SS and TS images were obtained using a previously developed nonlinear image-warping technique. The depiction ability of SS and TS images was evaluated using the contrast-to-noise ratio (CNR). The proportion of Top 1 SS images showing higher CNR than that of the TS images with 2- and 7-year acquisition intervals was 28% (28/100) and 33% (33/100), respectively. Moreover, the proportion of cases that had any of the Top 10 SS images with higher CNRs than those of TS images with 2- and 7-year acquisition intervals was 56% (56/100) and 72% (72/100), respectively. Our study indicates that the SS technique can potentially be used to detect lung nodules on CXRs.

Similar subtraction imaging is useful for the detection of lung nodules; however, some artifacts on similar subtraction images reduce their utility. The authors attempted to improve the image quality of similar subtraction images by reducing artifacts caused by differences in image contrast and sharpness between two images used for similar subtraction imaging. Image contrast was adjusted using the histogram specification technique. The differences in image sharpness were compensated for using a pixel matching technique. The improvement in image quality was evaluated objectively based on the degree of artifacts and the contrast-to-noise ratio (CNR) of the lung nodules. The artifacts in similar subtraction images were reduced in 94% (17/18) of cases, and CNR was improved in 83% (15/18) of cases. The results indicate that the combination of histogram specification and pixel matching techniques is potentially useful in improving image quality in similar subtraction imaging.

The luminance uniformity of liquid-crystal displays (LCDs) deteriorates with their prolonged use. In this paper, we present a method for evaluating the degree of luminance non-uniformity of LCDs with the use of a commercially available digital camera. In this study, seven monochrome LCDs, which were used during various operating times ranging from 5000 to 25,000 h, were evaluated with use of a camera. The maximum luminance deviation (MLD) was measured on the two-dimensional (2D) images obtained with the camera. In addition, an index of the luminance non-uniformity was calculated as the ratio of the area exhibiting luminance non-uniformity to the area of the entire LCD screen. We determined the area with the luminance non-uniformity by setting the allowable luminance deviation as the judgment criterion to evaluate the degree of luminance non-uniformity. The MLD values were less than 20% for all conditions, and they varied depending on the locations of the luminance measurement. The area ratios of the luminance non-uniformity based on 2D luminance distributions tended to increase with the duration of use of LCDs, and they indicated the degree of luminance non-uniformity of the LCDs regardless of the measurement locations. Our approach of using a commercially available digital camera showed its potential usefulness for providing more detailed and consistent evaluations of the degree of luminance non-uniformity of LCDs based on the 2D luminance distributions.

This paper describes the development of an automated method of extraction of biological fingerprints (BFs), including detection of image orientation in chest radiographs. The image orientation of a target image was recognized and modified by examination of normalized cross-correlation values between a target image and averaged male and female images with correct image orientation. Templates of BFs were extracted from averaged images. Then, each BF in the target image was extracted from locations that showed the highest cross-correlation value between the template of BF in the averaged image and the corresponding BF in the target image. With our method, 100% (200/200) of image orientations were recognized correctly. If the orientation was recognized as inappropriate, our algorithm modified it into the appropriate chest image orientation. In addition, the BFs automatically extracted from target images were improved. This method would be useful in a preprocessing system for patient recognition and identification.

In this study, three-dimensional phase contrast magnetic resonance imaging (3D-PC MRI), a novel technique, was validated to assess pulmonary artery (PA) flow in patients with chronic thromboembolic pulmonary hypertension (CTEPH). The MR data of PAs from 3D-PC and two-dimensional PC (2D-PC) from before and after treatment for 3 patients with CTEPH were retrospectively analyzed. Additionally, 3D- and 2D-PC MR scans of PA were performed in 5 healthy volunteers. Correlation of stroke volumes (SVs) obtained by 3D-PC and 2D-PC was analyzed using Pearson's correlation coefficients. There was an excellent correlation in the SV of main PA, left PA and right PA between 3D-PC and 2D-PC (main PA: r = 0.91, p < 0.01, left PA: r = 0.72, p < 0.01 and right PA: r = 0.77, p < 0.01). In conclusion, 3D-PC MRI was able to accurately quantify the PA flow in patients with CTEPH.

Quality assurance of electronic display devices is important for maintaining reliable soft-copy image interpretations. This paper presents effects of test patterns on measurement of the luminance of liquid-crystal display (LCD) devices by use of a telescopic-type luminance meter. The luminance for different types of test patterns having different backgrounds and measurement areas was measured and compared with the results obtained with AAPM task group-18 (TG-18) LN test patterns. The luminance measured for the test patterns with a black background was lower than that measured for TG-18 LN test patterns due to the light emitted from the outside the focused area of the telescopic-type luminance meter. Also, the luminance obtained with smaller measurement areas indicated lower luminance. These tendencies were particularly obvious at low luminance. The luminance of the LCD device by use of a telescopic-type luminance meter should be measured with test patterns that have a black background and a smaller measurement area than that for the TG-18 LN test patterns.