• Journal of Information Processing Systems
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• 제15권2호
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

• 대한방사선기술학회지:방사선기술과학
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• 제45권2호
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• pp.117-125
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• 2022

Although stationary inverse-geometry digital tomosynthesis (s-IGDT) is able to reduce motion artifacts, image acquisition time and radiation dose, the image quality of the s-IGDT is degraded due to the truncations arisen in projections. Therefore, the effects of geometric and image acquisition conditions in the s-IGDT should be analyzed for improving the image quality and clinical applicability of the s-IGDT system. In this study, the s-IGDT images were obtained with the various X-ray source arrangement types and the various number of projections. The resolution and noise characteristics of the obtained s-IGDT images were evaluated, and the characteristics were compared with those of the conventional DT images. The s-IGDT system using linear X-ray source arrangement and 40 projections maximized the image characteristics of resolution and noise, and the corresponding system was superior to the conventional DT system in terms of image resolution. In conclusion, we expect that the s-IGDT system can be used for providing medical images in diagnosis.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1126-1134
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• 2017

A variety of medical service applications in the field of the Internet of Things (IoT) are being studied. Segmentation is important to identify meaningful regions in images and is also required in 3D images. Previous methods have been based on gray value and shape. The Visible Korean dataset consists of serially sectioned high-resolution color images. Unlike computed tomography or magnetic resonance images, automatic segmentation of color images is difficult because detecting an object's boundaries in colored images is very difficult compared to grayscale images. Therefore, skilled anatomists usually segment color images manually or semi-automatically. We present an out-of-core 3D segmentation method for large-scale image datasets. Our method can segment significant regions in the coronal and sagittal planes, as well as the axial plane, to produce a 3D image. Our system verifies the result interactively with a multi-planar reconstruction view and a 3D view. Our system can be used to train unskilled anatomists and medical students. It is also possible for a skilled anatomist to segment an image remotely since it is difficult to transfer such large amounts of data.

• 한국멀티미디어학회논문지
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• 제23권3호
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• pp.468-475
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• 2020

In this paper, we proposed a three-dimensional visualization system for medical images in augmented reality based on deep learning. In the proposed system, the artificial neural network model performed fully automatic segmentation of the region of lung and pulmonary nodule from chest CT images. After applying the three-dimensional volume rendering method to the segmented images, it was visualized in augmented reality devices. As a result of the experiment, when nodules were present in the region of lung, it could be easily distinguished with the naked eye. Also, the location and shape of the lesions were intuitively confirmed. The evaluation was accomplished by comparing automated segmentation results of the test dataset to the manual segmented image. Through the evaluation of the segmentation model, we obtained the region of lung DSC (Dice Similarity Coefficient) of 98.77%, precision of 98.45%, recall of 99.10%. And the region of pulmonary nodule DSC of 91.88%, precision of 93.05%, recall of 90.94%. If this proposed system will be applied in medical fields such as medical practice and medical education, it is expected that it can contribute to custom organ modeling, lesion analysis, and surgical education and training of patients.

• 대한의용생체공학회:의공학회지
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• 제15권2호
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• pp.175-182
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• 1994

The international standard for digital compression and coding of continuous-tone still image known as JPEG (Joint Photographic Experts Group) standard is investigated for medical image archiving and communication. The JPEG standard has widely been accepted in the areas of electronic image communication, computer graphics, and multimedia applications, however, due to the lossy character of the JPEG compression its application to the field of medical imaging has been limited. In this paper, the JPEG standard is investigated for medical image compression with a series of head sections of magnetic resonance (MR) images (256 and 4096 graylevels, $256 {\times}256$size). Two types of Huffman codes are employed, i. e., one is optimized to the image statistics to be encoded and the other is a predetermined code, and their coding efficiencies are examined. From experiments, compression ratios of higher than 15 were obtained for the MR images without noticeable distortion. Error signal in the reconstructed images by the JPEG standard appears close to random noise. Compared to existing full-frame bit-allocation technique used for radiological image compression, the JPEG standard achieves higher compression with less Gibb's artifact. Feature of the progressive image build-up of the JPEG progressive coding may be useful in remote diognosis when data is transmitted through slow public communication channel.

• 한국CDE학회논문집
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• 제16권4호
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• pp.285-291
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• 2011

A pose estimation process from medical images is calculating locations and orientations of objects obtained from Computed Tomography (CT) volume data utilizing X-ray images from two directions. In this process, digitally reconstructed radiograph (DRR) images of spatially transformed objects are generated and compared to X-ray images repeatedly until reasonable transformation matrices of the objects are found. The DRR generation and image comparison take majority of the total time for this pose estimation. In this paper, a fast DRR generation technique based on GPU parallel computing is introduced. A volume ray-casting algorithm is explained with brief vector operations and a parallelization technique of the algorithm using Compute Unified Device Architecture (CUDA) is discussed. This paper also presents the implementation results and time measurements comparing to those from pure-CPU implementation and open source toolkit.

• Journal of Korean Neurosurgical Society
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• 제59권5호
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• pp.466-470
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• 2016

Objective : To determine imaging features that may separate adamantinomatous and papillary variants of craniopharyngiomas given that tumors with adamantinomatous signature features are associated with higher recurrence rates, morbidity, and mortality. We specifically reviewed calcification on CT, T1 bright signal intensity, and cystic change on T2 weighted images for differentiating these two types. Methods : We retrospectively reviewed the MRI and CT studies in 38 consecutive patients with pathologically proven craniopharyngiomas between January 2004 and February 2014 for the presence of calcification on CT scans, bright signal intensity on T1 weighted images, and cystic change on T2 weighted images. Results : Of the 38 craniopharyngiomas, 30 were adamantinomatous type and 8 were papillary type. On CT scans, calcification was present in 25 of 38 tumors. All calcified tumors were adamantinomatous type. Twenty four of 38 tumors had bright signal intensity on T1 weighted images. Of these 24 tumors, 22 (91.7%) were adamantinomatous and 2 were papillary type. Cystic change on T2 weighted images was noted in 37 of 38 tumors; only 1 tumor with papillary type did not show cystic change. Conclusion : T1 bright signal intensity and calcification on CT scans uniformly favor the adamantinomatous type over papillary type of craniopharyngioma in children. However, these findings are more variable in adults where calcification and T1 bright signal intensity occur in 70.6% and 58.8% respectively of adult adamantinomatous types of craniopharyngiomas.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2006년도 춘계종합학술대회
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• pp.163-166
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• 2006

컴퓨터의 발달과 의료기기의 디지털화로 인해 의료영상 분야도 디지털화되었다. 그 결과 디지털 의료영상의 불법복제, 소유권 및 데이터 인증 문제 또한 발생하고 있다. 이러한 환경 하에서 환자의 사생활 보호와 의료영상 자체의 소유권, 재산권의 여부 및 데이터 변형 여부의 판별을 위하여 디지털 워터마킹이 사용되고 있다. 기존에 제안된 여러 가지 워터마킹 기법들은 Non-Blind 방식에서는 원 영상이 필요하다는 점과 Blind 방식을 사용할 경우에는 육안으로는 식별이 힘든 양극 워터마크를 사용한다는 단점이 있다. 본 논문은 Blind 워터마킹에서 양극 워터마크를 삽입하는 방식을 따르지 않고, 시각적으로 인지하기 쉽도록 하기 위하여 이진 워터마크 영상을 다중 웨이블릿 변환하고, 원 영상을 이산 푸리에 변환하여 영상의 중간 주파수대에 Circular Input 방식을 이용하여 워터마크를 삽입하는 알고리즘을 제안하였고 그 방법은 상관도 0.97이라는 우수한 결과를 얻었다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2004년도 춘계종합학술대회
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• pp.241-246
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• 2004

일반 의료기관에서의 PACS를 이용한 효율적인 환자 영상의 관리가 늘어가고 있다. 그런 환경 하에서 환자의 사생활 보호와 의료영상 자체의 소유권, 재산권의 여부 및 데이터 변형여부의 판별이 중요시된다. 의료데이터의 보호를 위해 디지털 워터마킹이 사용되며, 본 논문에서는 RST공격에 강인한 워터마킹 기법을 제안한다. 기존에 제안된 기하학적 변형에 강인한 워터마킹 기법 중에서 Log-Polar변환과 Fourier-Mellin 변환을 이용한 방법은 영상에 가해진 RST공격을 영상의 좌표변환과 DFT의 순환적 이동 특성을 이용하여 강인성을 확보한다. 하지만 실제적 구현에서 원영상과 워터마크의 손실이 문제 시 된다. 본 논문에서는 반지름-위상 Look Up Table을 이용하여 좌표변환 시 발생하는 손실을 없애고, 각종 공격에 강인한 블라인드 워터마킹 기법을 제안한다.