Publications (10)0 Total impact
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ABSTRACT: The patient was a 18-year-old woman. Past history included right nephrectomy for right congenital hydronephrosis when she was an infant of 40 days. On examination, her blood pressure was 220/140 mmHg, and plasma renin activity was 4.2 ng/ml/hr. The selective renal arteriogram showed fibromuscular dysplasia of the left main renal artery, and a diagnosis of renovascular hypertension in the solitary kidney with an aberrant artery was made. Treatment with orally-active inhibitor of angiotensin I converting enzyme, Captopril, was started. Her blood pressure became normal after oral administration of Captopril, but her renal function deteriorated. Therefore, percutaneous transluminal angioplasty was performed twice resulting in effective dilatation of the stenotic portion of the left main renal artery. Thereafter, her blood pressure fluctuated between 170/120 and 140/70 mmHg. Eight months later, her blood pressure is now being controlled with mild antihypertensive treatment.
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ABSTRACT: 近年、医療分野における光学装置の発展は著しいものがある。CT、MRI、CRや超音波等の撮影機器により、撮影時間の大幅な低減や画像分解能の向上が図られるようになった。これにより、患者のX線被曝量は減少し、画像上に微細な病変を投影することが可能となり、診断の効率化が図られるようになった。しかし、読影すべきスライス枚数は増加し、医師の負担は多大なものとなっており、疲労などによる病巣部の見落としが懸念されている。そこで、医師への診断支援を行うためのCADシステムが開発されているが、病巣部の自動抽出に関しては、FP(False Positive)やFN(False Negative)の低減が問題として残っており、いまだ実用化の域に達していない分野が数多く存在している。本研究では、胸部CT画像から肺野領域のセグメンテーションを行い、抽出される関心領域内の病巣部候補領域を自動抽出する診断システムを構築した。また診断結果は、2次元及び3次元CT画像にマーキングを行う。提案法を胸部MDCT画像12症例に適用し、良好な結果を得た。; Recently, optical device such as CT, MRI, CR, and some other devices are developed in medical field. These devices provide us advantages that filming time decrease and image resolution is higher than past system. Simultaneously, exposure time is shorter than before. But slices which medical doctor should diagnosis are increase. By this reason, their burden is huge and oversight of abnormal area may be caused. On the other hand, segmentation for region of interest is important task to extract abnormal area correctly. In this paper, we propose a method for segmentation and extracting abnormal area on obtained lung region employing thorax Multi-detector raw CT images. Furthermore, extracted abnormal areas are marked and display on PC. We applied our technique onto 12 real MDCT images and satisfactory results are obtained. To analyze the experimental results, we evaluate our systems based on ROC analysis.
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