• Title/Summary/Keyword: 반치(反治)

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"의학입문(醫學入門)"에 나타난 삼음삼양(三陰三陽)과 표본중(標本中)에 대한 고찰(考察) 대(對)"의학입문(醫學入門)" 중출현적삼음삼양급표본중적연구(中出現的三陰三陽及標本中的硏究)

  • Jo, Hak-Jun
    • Journal of Korean Medical classics
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    • v.18 no.4 s.31
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    • pp.15-26
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    • 2005
  • 통과연구(通過硏究)${\ulcorner}$의학입문(醫學入門)${\lrcorner}$중대어삼음삼양각자이육기배속원리(中對於三陰三陽各自以六氣配屬原理), 육기납지(六氣納支), 절기방위(節氣方位), 표본음양속성(標本陰陽屬性), 경맥납지(經脈納支), 맥체(脈體), 치법(治法), 중기등진행분류급고찰(中氣等進行分類及考察), 득출결론여하(得出結論如下) : 1. 삼음삼양적속성여지지적배속불일치(三陰三陽的屬性與地支的配屬不一致). 태양화궐음수연이지지여진술화사해(太陽和厥陰雖然以地支與辰戌和巳亥), 인신상배속(寅申相配屬), 단시실제상표본적음양속성여납지적원리시부동적(但是實際上標本的陰陽屬性與納支的原理是不同的). 인차(因此), 재구별표본음양적특성상(在區別標本陰陽的特性上), 절기(節氣), 방위등불능성위일정기준(方位等不能成爲一定基準). 2. 삼음삼양본기적오행속성화경맥납지(三陰三陽本氣的五行屬性和經脈納支), 유가능불일치(有可能不一致). 양명조금지본(陽明操金之本), 불시수양명대장(不是手陽明大腸), 실제상족양명위재시본(實際上足陽明胃才是本), 소양상화지본(少陽相火之本), 역불시수소양삼초(亦不是手少陽三焦), 실제상족소양담재본(實際上足少陽膽才本). 3. 삼음삼양안조종화규율기치법각이(三陰三陽按照從化規律其治法各異). 제일(第一), 표여본적음양속성상반시용반치법(標與本的陰陽屬性相反時用反治法). 소음본열표한(少陰本熱標寒), 태양본한표열(太陽本寒標熱), 차한열부정(且寒熱不定), 고태양열인한용(故太陽熱因寒用), 이소음한인열용(而少陰寒因熱用). 제이(第二), 표여본적음양속성상동시용정치법(標與本的陰陽屬性相同時用正治法). 태음표본균한(太陰標本均寒), 소양표본균열(少陽標本均熱), 고태음한인한용(故太陰寒因寒用), 색인색용(塞因塞用), 이소양통인통용(而少陽通因通用). 제삼(第三), 표여본적음양속성상반(標與本的陰陽屬性相反), 차여중기적음양속성부동시(且與中氣的陰陽屬性不同時), 불능용정치혹반치법(不能用正治或反治法), 응구종어중진행치료(應驅從於中進行治療). 즉불능구니어궐음화양명적소정치법(卽不能拘泥於厥陰和陽明的所定治法), 응수기종중진행치료(應隨機從中進行治療). 4. ‘소음태양(少陰太陽) 종본종표(從本從標)’ 재응용어치료시(在應用於治療時), 가해석여하(可解釋如下): 제일(第一), 혹자종본(或者從本), 혹자종표(或者從標). 제이(第二), 혹자종본(或者從本), 혹자종표(或者從標), 단치료상유기선후지별(但治療上有其先後之別). 제삼(第三), 소음한인열용(少陰寒因熱用). 태양열인한용(太陽熱因寒用), 고동시구종어표본(故同時驅從於標本). 5. 재(在)‘양명궐음(陽明厥陰) 부종표본(不從標本) 종호중(從乎中)’적(的)‘종호중(從乎中)’, 가이해위재치법운용중가이(可理解爲在治法運用中可以)‘수기취중(隨機取中)’지의(之意).

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Evaluation of SharpIR Reconstruction Method in PET/CT (PET/CT 검사에서 SharpIR 재구성 방법의 평가)

  • Kim, Jung-Yul;Kang, Chun-Koo;Park, Hoon-Hee;Lim, Han-Sang;Lee, Chang-Ho
    • The Korean Journal of Nuclear Medicine Technology
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    • v.16 no.1
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    • pp.12-16
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    • 2012
  • Purpose : In conventional PET image reconstruction, iterative reconstruction methods such as OSEM (Ordered Subsets Expectation Maximization) have now generally replaced traditional analytic methods such as filtered back-projection. This includes improvements in components of the system model geometry, fully 3D scatter and low noise randoms estimates. SharpIR algorithm is to improve PET image contrast to noise by incorporating information about the PET detector response into the 3D iterative reconstruction algorithm. The aim of this study is evaluation of SharpIR reconstruction method in PET/CT. Materials and Methods: For the measurement of detector response for the spatial resolution, a capillary tube was filled with FDG and scanned at varying distances from the iso-center (5, 10, 15, 20 cm). To measure image quality for contrast recovery, the NEMA IEC body phantom (Data Spectrum Corporation, Hillsborough, NC) with diameters of 1, 13, 17 and 22 for simulating hot and 28 and 37 mm for simulating cold lesions. A solution of 5.4 kBq/mL of $^{18}F$-FDG in water was used as a radioactive background obtaining a lesion of background ratio of 4.0. Images were reconstructed with VUE point HD and VUE point HD using SharpIR reconstruction algorithm. For the clinical evaluation, a whole body FDG scan acquired and to demonstrate contrast recovery, ROIs were drawn on a metabolic hot spot and also on a uniform region of the liver. Images were reconstructed with function of varying iteration number (1~10). Results: The result of increases axial distance from iso-center, full width at half maximum (FWHM) is also increasing in VUE point HD reconstruction image. Even showed an increasing distances constant FWHM. VUE point HD with SharpIR than VUE point HD showed improves contrast recovery in phantom and clinical study. Conclusion: By incorporating more information about the detector system response, the SharpIR algorithm improves the accuracy of underlying model used in VUE point HD. SharpIR algorithm improve spatial resolution for a line source in air, and improves contrast recovery at equivalent noise levels in phantoms and clinical studies. Therefore, SharpIR algorithm can be applied as through a longitudinal study will be useful in clinical.

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