@misc{oai:kumadai.repo.nii.ac.jp:00024190,
 author = {Oda, Seitaro and 尾田, 済太郎},
 month = {Mar},
 note = {application/pdf, 学位論文(Thesis), 1)We investigated the clinical efficacy of
DES technique using FPD chest radiography systems in the detection of small
pulmonary nodules. We also investigated the effect of virtual DES image using the
massive-training artificial neural network (MTANN) which is a kind of artificial
intelligence. 2)We investigated the accuracy and
reproducibility of computer-aided volumetry (CAV) software for GGO nodules.Moreover, we evaluated the volume-doubling time (VDT) of histologically proved
GGO nodules., ①近年、flat-panel detector (FPD) X線装置に応用されたdual-energy subtraction (DES)技術を使用して、小型肺結節の検出能について検討した。また、人工知能の一種であるmassive
training artificial neural network (MTANN)を応用したvirtual DES 技術の有用性についても検討した。
②GGO 結節におけるコンピュータ支援３次元的体積測定の精度を検証し、続いてGGO 結節のvolume doubling time（VDT）について検討を行った。},
 title = {Radiological Analysis for the Detection and Qualitative Diagnosis of Small Pulmonary Nodules},
 year = {2010}
}