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Early diagnosis of malignant-transformed ovarian mature cystic teratoma: fat-suppressed MRI findings
Hiroshi Takagi,Satoshi Ichigo,Takayuki Murase,Tsuneko Ikeda,Atsushi Imai 대한부인종양학회 2012 Journal of Gynecologic Oncology Vol.23 No.2
The most common form of malignant transformation developing from a mature cystic teratoma is squamous cell carcinoma,representing 80% of malignant transformations, while adenocarcinoma accounts for approximately 5%. Because of this rarity,few reports exist of preoperative diagnosis of this tumor by magnetic resonance imaging, in particular with fat suppression techniques. Here, we report magnetic resonance imaging findings and clinical features of a 79-year-old woman with mucinous adenocarcinoma arising from a mature cystic teratoma (measuring 5×6 cm), classified as surgical stage IA. Because of the poor prognosis of malignant transformation, when mature cystic teratomas are detected (even smaller than 5 cm tumor size)in postmenopausal women, serum tumor marker carcinoembryonic antigen levels and fat-suppressed magnetic resonance imaging may be potential indicators of malignant transformation.
Hiroshi Mizumoto,Masao Imai,Yoshito Yabuta,Shiroh Arii 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
A new type of touch probe for measuring small optical parts is proposed. The probe is excited by a piezoelectric actuator in sinusoidal waveform. When the vibrating probe touches an object, harmonic components of the vibration appear in the power spectrum of the probe vibration. When the power of the second harmonic exceeds a threshold level, it is judged that the probe touches the object. Measuring force is small enough for measuring the surface of optical parts. The touch probe is mounted on a small CMM controlled by a PC and evaluated its performance by measuring a standard steel ball.
Quadrilateral mesh fitting that preserves sharp features based on multi-normals for Laplacian energy
Imai, Yusuke,Hiraoka, Hiroyuki,Kawaharada, Hiroshi Society for Computational Design and Engineering 2014 Journal of computational design and engineering Vol.1 No.2
Because the cost of performance testing using actual products is expensive, manufacturers use lower-cost computer-aided design simulations for this function. In this paper, we propose using hexahedral meshes, which are more accurate than tetrahedral meshes, for finite element analysis. We propose automatic hexahedral mesh generation with sharp features to precisely represent the corresponding features of a target shape. Our hexahedral mesh is generated using a voxel-based algorithm. In our previous works, we fit the surface of the voxels to the target surface using Laplacian energy minimization. We used normal vectors in the fitting to preserve sharp features. However, this method could not represent concave sharp features precisely. In this proposal, we improve our previous Laplacian energy minimization by adding a term that depends on multi-normal vectors instead of using normal vectors. Furthermore, we accentuate a convex/concave surface subset to represent concave sharp features.
Quadrilateral Mesh Fitting that Preserves Sharp Features based on Multi-Normals for Laplacian Energy
Yusuke Imai,Shogo Moriya,Hiroyuki Hiraoka,Hiroshi Kawaharada (사)한국CDE학회 2013 한국CAD/CAM학회 국제학술발표 논문집 Vol.2010 No.8
Nowadays, manufacturers use computer-aided design for simulations. The reason is that the cost of performance test using actual products is expensive, so the cost of performance simulation using CAD models is lower than it. In this paper, we think about hexahedral meshes for finite element analysis, because simulations with hexahedral mesh are more accurate than those with tetrahedral meshes. Our purpose is automatic hexahedral mesh generation with sharp features to precisely represent the corresponding features of a target shape. Our hexahedral mesh is generated by a voxel-based algorithm. Thus, in our previous works, we fit the surface of the voxels to the target surface using Laplacian energy minimization. We used normal vector in the fitting for preserving sharp features. However, the method can not represent concave sharp features precisely. Thus, we improve the previous Laplacian energy by adding a term that depends on multi-normal vectors instead of a term using normal vectors. Furthermore, we accentuate convex/concave subset of surface to represent concave sharp features.