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구강 암종에서 인체 유두종 바이러스 DNA 검출 및 p53 단백의 과발현과의 상관관계
서찬호(Chan Ho Seo),이영수(Young Soo Lee),심광섭(Kwang Sup Shim),유광희(Kwang Hee Yoo) 대한구강악안면외과학회 1997 대한구강악안면외과학회지 Vol.23 No.3
Epidemiological evidence suggests that human papillomavirus(HPV) infection is a high risk factor for the development of oral cancers. Many oncogenes, especially p53 suppressor gene, have a critical role of carcinogenesis in several human cancers including oral cancers. To investigate the prevalence of HPV infection and subtyping of high risk group(HPV-16, -18 and -33) HPV in oral cancers, the author studied 31 cases of squamous cell carcinomas arising from the oral cavity using polymerase chain reaction (PCR). The author also demonstrated the overexpression of p53 oncoprotein in the oral cancers using immunohistochemical methods. The correlation between HPVs infection and p53 overexpression in tumorigenesis of the oral cancers was evaluated. 1. Twenty-one cases(66.7%) among 31 cases of oral squamous cell carcinomas were positive for HPV-DNA. Among them, 16 cases were positive for HPV-16, 4 cases for HPV-18, and 2 cases for HPV-33. Two cases were coinfected with HPV-16 and HPV-18, and HPV-18 and HPV-33. 2. The prevalence of HPV infection appeared not correlated with tumor differentiation and clinical stages of oral squamous cell carcinomas. 3. The overexpression of p53 oncoprotein was present in 24 of 31 cases(77%). In 21 HPV positive tumors 18 cases were positive for overexpression of p53 oncoprotein. Six cases were positive for p53 in ten HPV negative tumors. There was no correlation between HPV DNA detection rate and p53 overexpression. The above results suggest that HPV infection and p53 oncogene mutation play different roles in tumorigenesis of oral squamous cell carcinomas. No coexpression of p53 oncoprotein with HPV-DNA detection suggests that another etiologic mechanism other than HPV infection may be operative.
NeRF의 정확한 3차원 복원을 위한 거리-엔트로피 기반 영상 시점 선택 기술
최진원,서찬호,최준혁,최성록 한국로봇학회 2024 로봇학회 논문지 Vol.19 No.1
This paper proposes a new approach with a distance-based regularization to the entropy applied to the NBV (Next-Best-View) selection with NeRF (Neural Radiance Fields). 3D reconstruction requires images from various viewpoints, and selecting where to capture these images is a highly complex problem. In a recent work, image acquisition was derived using NeRF's ray-based uncertainty. While this work was effective for evaluating candidate viewpoints at fixed distances from a camera to an object, it is limited when dealing with a range of candidate viewpoints at various distances, because it tends to favor selecting viewpoints at closer distances. Acquiring images from nearby viewpoints is beneficial for capturing surface details. However, with the limited number of images, its image selection is less overlapped and less frequently observed, so its reconstructed result is sensitive to noise and contains undesired artifacts. We propose a method that incorporates distance-based regularization into entropy, allowing us to acquire images at distances conducive to capturing both surface details without undesired noise and artifacts. Our experiments with synthetic images demonstrated that NeRF models with the proposed distance and entropy-based criteria achieved around 50 percent fewer reconstruction errors than the recent work.