• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1296-1301
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• 2008

Ultrasonography constructs pictures of areas inside the body needs in diagnosis by bouncing high-enorgy sound waves(ultrasound) off internal tissues or organs. In constructing an ultrasonographic image, the weakness of bounding signals induces noises and detailed differences of brightness, so that having a difficulty in detecting and diagnosing with the naked eyes in the analysis of ultrasonogram. Especially, the difficulty is extended when diagnosing muscle areas by using ultrasonographic images in the musculoskeletal test. In this paper, we propose a novel image processing method that computationally extracts a muscle area from an ultrasonographic image to assist in diagnosis. An ultrasonographic image consists of areas corresponding to various tissues and internal organs. The proposed method, based on features of intensity distribution, morphology and size of each area, extracts areas of the fascia, the subcutaneous fat and other internal organs, and then extracts a muscle area enclosed by areas of the fascia. In the extraction of areas of the fascia, a series of image processing methods such as histogram stretching, multiple operation, binarization and area connection by labeling is applied. A muscle area is extracted by using features on relative position and morphology of areas for the fascia and muscle areas. The performance evaluation using real ultrasonographic images and specialists' analysis show that the proposed method is able to extract target areas being approximate to real muscle areas.

• Investigative Magnetic Resonance Imaging
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• v.17 no.3
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• pp.192-199
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• 2013

Purpose : To retrospectively evaluate the diagnostic performance of dynamic contrast-enhanced MR imaging (DCE-MRI) in detecting recurrent prostate cancer after HIFU of clinically localized cancer, as compared with T2-weighted imaging (T2WI). Materials and Methods: Twenty-six patients with increased prostate-specific antigen levels after HIFU were included in this study. All MR examinations were performed using T2WI and DCE-MRI, followed by transrectal ultrasound-guided biopsy. MRI and biopsy results were correlated in six prostate sectors. Residual or recurrent cancer after HIFU was defined as local tumor progression if biopsy results showed any cancer foci. Two independent readers interpreted the MR images. Results: Of 156 prostate sectors, 51 (33%) were positive for cancer in 17 patients. For detecting local tumor progression, the sensitivity of DCE-MRI and T2WI was 80% and 57% for reader 1 (P < 0.001) versus 84% and 61% for reader 2 (P < 0.001), respectively. The specificity and overall accuracy between DCE-MRI and T2WI showed no statistical difference in both readers (P > 0.05). Interobserver agreement of DCE-MRI and T2WI was moderate and fair, respectively. Conclusion: For detecting local tumor progression of prostate cancer after HIFU, DCE-MRI was more sensitive than T2WI, with less interobserver variability.

• Korean Journal of Optics and Photonics
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• v.31 no.1
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• pp.1-6
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• 2020

The chest wall, an organ directly affected by environmental particles through respiration, consists of ribs, a pleural layer and intercostal muscles. To diagnose early and treat disease in this body part, it is important to visualize the details of the chest wall, but the structure of the pleural layer cannot be seen by chest computed tomography or ultrasound. On the other hand, optical coherence tomography (OCT), with a high spatial resolution, is suited to observe pleural-layer response to talc, one of the fine materials. However, intensity-based OCT is weak in providing information to distinguish the detailed structure of the chest wall, and cannot distinguish the reaction of the pleural layer from the change in the muscle by the talc. Polarization-sensitive OCT (PS-OCT) takes advantage of the fact that specific tissues like muscle, which have optical birefringence, change the backscattered light's polarization state. Moreover, the birefringence of muscle associated with the arrangement of myofilaments indicates the muscle's condition, by measuring retardation change. The PS-OCT image is interpreted from three major perspectives for talc-exposure chest-wall imaging: a thickened pleural layer, a separation between pleural layer and muscle, and a phase-retardation measurement around lesions. In this paper, a rabbit chest wall after talc pleurodesis is investigated by PS-OCT. The PS-OCT images visualize the pleural layer and muscle, respectively, and this system shows different birefringence of normal and damaged lesions. Also, an analyisis based on phase-retardation slope supports results from the PS-OCT image and histology.