• Journal of Magnetics
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• v.21 no.1
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• pp.148-152
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• 2016

The main goal was to evaluate effectiveness of a modified TSE sequence compared with DIR (double inversion recovery) sequence in acquisition of fast flow brain vessel images using signal void effect. 32 healthy volunteers (10 men and 22 women; mean age of 31 years; ranging between 28-43 years) who underwent black blood DIR sequence (group A) and the modified TSE sequence (group B) were enrolled in our study. Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) of the internal carotid arteries' lumen were compared in T1 and T2 weighted images for both group A and B. The images obtained from group B showed lower SNR values in internal carotid artery than the group A in both of the T1 and T2 weighted images (11.49% and 13.66% respectively). While the CNR values were higher in the group B than the group A in both of the T1 and T2 weighted images (8.69% and 7.55 % respectively). The qualitative score of all categories were not significantly different between the two groups. Furthermore approximately 49% of the total scan time was reduced from group B. Our study is to shorten the scanning time and minimize the inconveniences of the patients in acquisition of the black blood images of brain by using the signal void effect in the modified TSE technique while keeping the diagnostic value of the test.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.355-364
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• 2018

When focusing using an ultrasonic transducer array, a main lobe is formed in the focal region of an ultrasound field, but side lobes also arise around the focal region due to the leakage. Since the side lobes cannot be completely eliminated in the focusing process, they are responsible for subsequent ultrasound image quality degradation. To improve ultrasound image quality, a signal processing strategy to reduce side lobes is definitely in demand. To this end, quantitative determination of main and side lobes is necessary. We propose a theoretically and actually error-free method of exactly discriminating and separately computing the main lobe and side lobe parts in ultrasound image by computer simulation. We refer to images constructed using the main and side lobe signals as the main and side lobe images, respectively. Since the main and side lobe images exactly represent their main and side lobe components, respectively, they can be used to evaluate ultrasound image quality. Defining the average brightness of the main and side lobe images, the conventional to side lobe image ratio, and the main to side lobe image ratio as image quality metrics, we can evaluate image characteristics in speckle images. The proposed method is also applied in assessing the performance of side lobe suppression filtering. We show that the proposed method may greatly aid in the evaluation of medical ultrasonic images using computer simulations, albeit lacking the use of actual experimental data.

• Korean Journal of Veterinary Research
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• v.62 no.1
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• pp.8.1-8.6
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• 2022

The aim of this prospective study was to investigate the effects of focal spot size of X-ray tube on sharpness of clinical radiographic images of dogs and cats. Radiographic images of 24 stifle joints, 15 carpi, 18 lumbar spines, 61 thoraxes, and 47 abdomens of 102 dogs and 4 cats were obtained in the present study, using 2 X-ray tubes with nominal focal spots of 2.0 mm and 0.6 mm, respectively. The sharpness of specific anatomical structures in all the images of 5 projections was assessed. The radiographic sharpness of various anatomical structures of lumbar spine and cortex of stifle with fine focal spot was increased significantly compared with broad focal spot images. In addition, the blurred motion was significantly higher in the fine focal spot images of thorax. In conclusion, our study suggests that a selective use of fine foci for imaging of lumbar spine or cortex of stifle enhanced radiographic sharpness.

• Journal of Biomedical Engineering Research
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• v.30 no.1
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• pp.34-40
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• 2009

Transforms including translation and rotation are required for registering two or more images. In medical applications, different registration methods have been applied depending on the structures: for rigid bodies such as bone structures, affine transformation was widely used. In most previous research, a single transform was used for registering the whole images, which resulted in low registration accuracy especially when the degree of deformation was high between two images. In this paper, a novel registration method is introduced which is based image sub-division and bilinear interpolation of transformations. The proposed method enhanced the registration accuracy by 40% comparing with Trimmed ICP for registering color and MRI images.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.185-191
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• 2005

In this paper, we proposed a downscaled 3D object technique using medical images for telediagnostic use. The proposed system consisted of downscaling/thresholding processes for building a downscaled 3D object and a process for obtaining 2D images at specific angles for diagnosis support. We used 80 slices of Digital Imaging and Communication in Medicine(DICOM) CT images as sample images and the platform-independent Java language for the experiment. We confirmed that the total image set size and transmission time of the original DICOM image set using a down-scaled 3D object decreased approximately $99\%\;and\;98.41\%,$ respectively. With additional studies, the proposed technique obtained from these results will become useful in supporting diagnosis for home and hospital care.

• Journal of Biomedical Engineering Research
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• v.26 no.3
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• pp.133-138
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• 2005

This paper presents a new method for measuring ocular torsion using the optical flow. Images of the iris were cropped and transformed into rectangular images that were orientation invariant. Feature points of the iris region were selected from a reference and a target image, and the shift of each feature was calculated using the iterative Lucas-Kanade method. The feature points were selected according to the strength of the corners on the iris image. The accuracy of the algorithm was tested using printed eye images. In these images, torsion was measured with $0.15^{\circ}$ precision. The proposed method shows robustness even with the gaze directional changes and pupillary reflex environment of real-time processing.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.106-109
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• 2009

Recently, image matching becomes important in Computer Aided Diagnosis (CAD) due to the huge amount of medical images. Specially, texture feature is useful in medical image matching. However, texture features such as co-occurrence matrices can't describe well the spatial distribution of gray levels of the neighborhood pixels. In this paper we propose a frequency domain-based texture feature extractor that describes the local spatial distribution for medical image retrieval. This method is based on 2D Local Discrete Fourier transform of local images. The features are extracted from local Fourier histograms that generated by four Fourier images. Experimental results using 40 classes Brodatz textures and 1 class of Emphysema CT images show that the average accuracy of retrieval is about 93%.

• Progress in Medical Physics
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• v.32 no.2
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• pp.50-58
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• 2021

Purpose: In this study, we investigated the relationship between the noise characteristics and the number of projected images in tomosynthesis using a digital phantom. Methods: The digital phantom consisted of a columnar phantom in the center of the image and a spherical phantom with a diameter of 80 pixels. A virtual scan was performed, and 128 projected images (Tomo_w/o) of the phantoms were obtained. The image noise according to the Poisson distribution was added to the projected images (Tomo_×1). Furthermore, another projected image with additional noise was prepared (Tomo_×1/2). For each dataset, we created datasets with 64 (half) and 32 (quarter) projections by removing the even-numbered images twice from the 128 (fully) projected images. Tomosynthesis images were reconstructed by filtered back projection (FBP). The modulation transfer function (MTF) was estimated using the sphere method, and the noise power spectrum (NPS) was estimated using the two-dimensional Fourier transform method. Results: The MTFs did not change between datasets, and the NPSs improved as the number of projected images increased. The noise characteristics of the Tomo_×1_half images were the same as those of the Tomo_×1/2_full. Conclusions: To achieve a reduction in the patient dose in tomosynthesis acquisition, we recommend reducing the number of projected images rather than reducing the dose per projection.

• Imaging Science in Dentistry
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• v.46 no.3
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• pp.173-178
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• 2016

Purpose: Optical coherence tomography (OCT) has been investigated as a novel diagnostic imaging tool. The utilisation of this equipment has been evaluated through several studies in the field of dentistry. The aim of this preliminary study was to determine through basic experiments the effectiveness of OCT in implant dentistry. Materials and Methods: To assess detection ability, we captured OCT images of implants in each of the following situations: (1) implants covered with mucosae of various thicknesses that were harvested from the mandibles of pigs; (2) implants installed in the mandibles of pigs; and (3) implants with abutments and crowns fixed with temporary cement. The OCT images were captured before cementation, after cementation, and after removing the excess submucosal cement. Results: If the thickness of the mucosa covering the implant body was less than 1 mm, the images of the implants were clearly detected by OCT. In the implants were installed in pigs' mandibles, it was difficult to capture clear images of the implant and alveolar bone in most of the samples. Remnants of excess cement around the implants were visible in most samples that had a mucosa thickness of less than 3 mm. Conclusion: Currently, OCT imaging of implants is limited. Cement remnants at the submucosal area can be detected in some cases, which can be helpful in preventing peri-implant diseases. Still, though there are some restrictions to its application, OCT could have potential as an effective diagnostic instrument in the field of implant dentistry as well.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.